34 jobs found

The Disney Decision Science and Integration (DDSI) team leverages advanced technologies, data analytics, and scientific approaches such as optimization and statistical modeling to build innovative tools that shape business decisions across The Walt Disney Company. We support Disney Entertainment (ABC, The Walt Disney Studios, Disney+, Hulu), ESPN, Disney Experiences (Theme Parks, Cruise Line, Consumer Products, DVC), and Corporate Finance with strategic applications that enable data-driven decision-making. This team works in office. What You Will Do As the Ontology/Semantic Librarian, you will lead the design, development, and governance of enterprise ontologies, semantic layers, and knowledge graphs that serve as the intelligent backbone for a modern federated data platform. This role combines deep semantic modeling expertise with hands-on implementation of graph technologies, vector databases, and federated data architectures to accelerate business value delivery. This role will make key contributions to the Data Unification initiative by enabling rapid discovery and utilization of our vast data assets across the Disney enterprise. Design and build enterprise ontologies and semantic models that align business objectives with technical implementation, ensuring rapid enablement of business use cases such as unified reporting, AI agents, data marketplaces, and cross-functional insights. Lead the creation and maintenance of semantic layer graphs, knowledge graphs, and entity graphs, clearly distinguishing and leveraging the strengths of each approach. Develop and implement strategies for using vector databases and graph databases (e.g., Neo4j, Amazon Neptune, Qdrant, or similar) to enable powerful LLM-augmented search and reasoning over highly federated, heterogeneous data stores. Partner with data engineering, AI, and business teams to translate business goals into ontological models that drive measurable outcomes. Design and evolve the enterprise Data Catalog with rich semantic metadata, lineage, and governance capabilities. Contribute to the development of a unified data access layer that supports querying across Snowflake, Databricks, PostgreSQL, MongoDB, S3, Kafka, and other sources through a single semantic interface. Implement and enforce enterprise security models (RBAC/ABAC, column/row-level security, and dynamic masking) through the ontology and semantic layer. Collaborate on AI integration initiatives, including building ontology-driven agents, RAG pipelines, and agent-to-agent communication protocols. Establish ontology governance processes, versioning, and lifecycle management to ensure scalability and consistency across the enterprise. Contribute to the internal Data Marketplace by defining semantic data products with clear business value and consumption models. Mentor team members on semantic technologies and best practices for ontology-driven data architecture. Required Qualifications & Skills 7+ years of experience in data engineering, data architecture, semantic technologies, knowledge engineering, or related fields with a strong technical implementation background. Deep expertise in ontology modeling (OWL, RDF, SKOS, SHACL) and graph technologies. Strong understanding of the differences between semantic layer graphs, knowledge graphs, and entity graphs and when to apply each. Hands-on experience with graph databases (Neo4j, Neptune, etc.) and vector databases for semantic search and LLM integration. Proficiency in designing and implementing Data Catalogs and semantic metadata management solutions. Experience building solutions on top of federated data architectures involving relational (PostgreSQL, Snowflake), document (MongoDB), object (S3), and streaming (Kafka) systems. Demonstrated ability to translate complex business goals into ontological designs that accelerate delivery of business value. Strong programming skills, particularly Python, SPARQL, Cypher, GraphQL, and SQL. Experience with modern data platforms, cloud services (AWS preferred), and infrastructure-as-code practices. Solid understanding of data governance, security (RBAC/ABAC, dynamic masking), and compliance in enterprise environments. Excellent communication skills with the ability to bridge business stakeholders and technical teams. Desired Qualifications Experience building ontologies in large, complex enterprises (especially with media, entertainment, hospitality, or consumer-focused businesses). Hands-on experience with Generative AI, LLMs, RAG architectures, and agentic systems. Familiarity with data marketplace or data product platforms. Prior work with Apache Iceberg, Trino/Presto, or similar federated query engines. Knowledge of semantic web standards and tools (Protégé, TopBraid, Stardog, etc.). Background in formal knowledge representation, taxonomy development, or master data management. Required Education Bachelor's degree and/or equivalent work experience Preferred Education Bachelor's degree in Computer Science, Information Systems, Data Science, Philosophy (with logic focus), Linguistics, or a related technical field (or equivalent experience). Master's degree or PhD in a relevant field (Semantic Technologies, AI, Data Science, or Computer Science). The hiring range for this position in Lake Buena Vista, FL is $148,300 to $198,800 per year, in Burbank, CA is $155,700 to $208,700 per year, and New York, NY or Seattle, WA is $163,100 to $218,700 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.

Disney Entertainment and ESPN Product & Technology Technology is at the heart of Disney's past, present, and future. Disney Entertainment and ESPN Product & Technology is a global organization of engineers, product developers, designers, technologists, data scientists, and more - all working to build and advance the technological backbone for Disney's media business globally. The team marries technology with creativity to build world-class products, enhance storytelling, and drive velocity, innovation, and scalability for our businesses. We are Storytellers and Innovators. Creators and Builders. Entertainers and Engineers. We work with every part of The Walt Disney Company's media portfolio to advance the technological foundation and consumer media touch points serving millions of people around the world . Here are a few reasons why we think you'd love working here: Building the future of Disney's media: Our Technologists are designing and building the products and platforms that will power our media, advertising, and distribution businesses for years to come. Reach, Scale & Impact: More than ever, Disney's technology and products serve as a signature doorway for fans' connections with the company's brands and stories. Disney+. Hulu. ESPN. ABC. ABC News and many more. These products and brands - and the unmatched stories, storytellers, and events they carry - matter to millions of people globally . Innovation: We develop and implement groundbreaking products and techniques that shape industry norms, and solve complex and distinctive technical problems. The Data Product team is seeking a Senior Product Manager II to drive measurement strategy and analytics instrumentation across ESPN's portfolio of digital products. The team sits at the intersection of the analytics and business teams who depend on trusted data and the engineering teams who build the systems that produce it - and this role is where those worlds meet. You'll own instrumentation outcomes across ESPN digital products driving measurement strategy, schema design, and end-to-end delivery across web, mobile, and connected TV. The scope runs the full lifecycle: from defining what gets measured and why, through implementation and validation support, to ensuring downstream teams have the reliable, well-documented data they can build on. Own data collection outcomes for ESPN's digital products - accountable for completeness, accuracy, and usability across your instrumentation domain. Define what gets measured, why it matters, and how behavioral signals and event schemas serve analytics, reporting, and experimentation needs. Convert stakeholder questions into precise instrumentation specs - events, parameters, identifiers, schemas - that engineers can implement without ambiguity across platforms. Drive instrumentation from discovery through launch, orchestrating delivery across Product Engineering, Analytics Engineering, QA, and Platform partners. Work directly with engineering to ensure instrumentation is implemented correctly and meets platform standards - the bridge between measurement intent and technical reality. Configure and operate the analytics platform stack hands-on: implementation, maintenance, and optimization to support reliable, self-service analysis. Proactively identify instrumentation gaps and drive resolution through sharper specs, stronger validation, and tight coordination with engineering and QA. Use data to audit tagging and tracking health, surface improvement opportunities, and shape future measurement decisions. Mentor peer PMs and share instrumentation expertise across the team. You bring deep technical fluency in data collection and instrumentation, strong judgment about what measurement actually matters, and the communication skills to align engineers, analysts, and business leaders. You hold yourself to a standard of data quality that makes the difference between insights organizations trust and data they work around. Basic Qualifications 7 years or more in analytics instrumentation, data product management, or analytics engineering - with a track record of owning outcomes, not just executing tasks Deep hands-on experience designing event-based data models and instrumentation schemas across web, mobile, and connected TV - including event taxonomies, parameter design, identifier strategies, and implementable data contracts Ability to translate ambiguous business questions into precise instrumentation specifications - closing the gap between what stakeholders need to know and what engineers build SQL fluency and hands-on experience in cloud data platforms (Snowflake, Databricks, BigQuery , or equivalent) to validate data quality, investigate anomalies, and own your analysis Experience configuring and operating enterprise analytics platforms at scale - owning implementation, validation, and maintenance, not just strategy Proven ability to orchestrate cross-functional instrumentation delivery across Product Engineering, Analytics, QA, and platform partners A bias for action and an ownership mindset: you solve problems end-to-end and are equally comfortable debugging a data issue and presenting measurement strategy to senior leadership You use AI-enabled tools as a genuine force multiplier - this is how you work, not a skill you're developing Clear, crisp communication: precise technical specs, accessible explanations of instrumentation tradeoffs for non-technical stakeholders, and the ability to influence across engineering, product and analytics Preferred Qualifications Experience with sports, media, or direct-to-consumer digital products at scale Hands-on experience implementing solutions from Adobe's Customer Experience (CX) Analytics suite - Adobe Analytics, Customer Journey Analytics, or Adobe Experience Platform - at enterprise scale Expert understanding of media industry measurement solutions (Nielsen, Comscore ) and how they're implemented and integrated within a major media organization Familiarity with event-driven architectures or streaming data infrastructure and their connection to downstream analytics Experience enabling self-service analytics at scale through standardized metrics frameworks, reporting taxonomies, or dashboarding solutions Working knowledge of data governance, privacy, and consent frameworks (GDPR, CCPA) and their practical implications for instrumentation design Required Education Bachelor's degree in computer science, Engineering, Business, Analytics, or related field, or equivalent practical experience. The hiring range for this position in Bristol, CT is $155,700 - $208,700 and New York City, NY is $163,100 - $218,700 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.

Required Qualifications 8+ years of experience in machine learning, data science, AI engineering, ML engineering, or related roles. Strong hands-on experience building, tuning, validating, and deploying ML models. Experience mentoring data scientists, ML engineers, data engineers, or analytics teams. Strong knowledge of supervised learning, unsupervised learning, classification, regression, forecasting, NLP, and model evaluation techniques. Experience with Python and common ML/data science libraries such as pandas, NumPy, scikit-learn, XGBoost, TensorFlow, PyTorch, or similar. Practical experience with MLOps concepts such as model registry, experiment tracking, CI/CD, deployment pipelines, monitoring, drift detection, and retraining. Experience working with enterprise data platforms, cloud platforms, and modern data engineering practices. Strong understanding of data quality, feature engineering, model validation, and production support. Ability to translate business problems into AI/ML solution designs. Strong communication skills with the ability to explain technical concepts to both technical and non-technical stakeholders. Technical Skills Programming: Python, SQL Machine Learning: scikit-learn, XGBoost, TensorFlow, PyTorch, statistical modeling, forecasting, NLP MLOps: MLflow, Azure ML, Dataiku, model registry, CI/CD, GitHub Actions Data Platforms: Snowflake, Azure SQL, Oracle, data lakes, cloud data platforms AI/GenAI: LLMs, prompt engineering, RAG, semantic search, text-to-SQL, document intelligence Governance: model documentation, lineage, metadata, data quality, responsible AI, privacy and security controls Desired Skills: Preferred Qualifications Experience in healthcare, dental insurance, health insurance, financial services, or another regulated industry. Experience with platforms such as Azure ML, Dataiku, Databricks, Snowflake, MLflow, GitHub, GitHub Actions, Power BI, or similar tools. Experience with GenAI and LLM-based solutions. Experience designing AI solutions using enterprise data platforms such as Snowflake or cloud-based data ecosystems. Experience with responsible AI, model governance, bias detection, explainability, and audit requirements. Experience supporting AI governance councils, architecture reviews, or model risk review processes. Experience with healthcare data domains such as members, providers, claims, benefits, eligibility, call center, clinical, dental, or operational data.

Hiring: Principal Infrastructure Engineer Location: San Francisco, CA (Hybrid) Employment Type: Contract (C2C/W2) Work Authorization: USC / H4 EAD / H1B Apply: We are looking for an experienced Principal Infrastructure Engineer to design and deploy scalable, secure infrastructure for Nextdata OS across multi-cloud environments. This is an exciting opportunity to work on Kubernetes-native technologies, cloud infrastructure, CI/CD automation, and large-scale distributed systems. Key Responsibilities Design and implement deployment models for PaaS, SaaS, and customer-managed environments. Build scalable Infrastructure-as-Code (IaC) solutions using modern cloud technologies. Develop and optimize CI/CD pipelines for cloud-native applications. Deploy and operate secure, highly available Kubernetes platforms across multi-cloud environments. Collaborate with customers, product teams, and engineering to deliver scalable infrastructure solutions. Drive platform reliability, observability, security, and performance optimization. Conduct infrastructure code reviews, security reviews, and architecture improvements. Support production environments and ensure operational excellence. Required Qualifications Bachelor's Degree in Computer Science, Engineering, or a related field. 8+ years of Infrastructure Engineering experience. Strong expertise in Kubernetes (EKS, GKE, AKS) and Docker. Hands-on experience with Infrastructure as Code (Terraform, CloudFormation). Experience with AWS, Azure, and GCP cloud platforms. Strong experience building CI/CD pipelines for cloud-native applications. Experience deploying and managing PaaS and SaaS platforms. Knowledge of data and ML platforms including Snowflake and Databricks. Experience with cloud networking (AWS VPC, Azure VNet, GCP VPC). Experience with observability tools (Prometheus, ELK Stack, Grafana, or similar). Experience with service mesh technologies such as Istio or Linkerd. Strong understanding of cloud security, scalability, reliability, and distributed systems. Excellent troubleshooting, automation, and customer-facing communication skills. Interested candidates, please share your updated resume to: Rachael IT Services Development Staffing Email: Direct:

Hi I hope you are doing well. We have an urgent position listed below. Please send your most recent resume along with the expected rate if you are interested. Job Role: Snowflake Solutions Architect Location: IFF office, Union Beach New Jersey (hybrid 3 days in a week (Tues, Wed & Thurs Visa: USC/GC/GC-EAD/TN-W2 Only Job Description: Mandatory Skills:- Snowflake Admin, DBT Admin, Solution Architect, Python, SQL, AWS Core Technical Skills Snowflake: architecture patterns, security/governance, optimisation, and operational best practices. AWS Data Analytics Services: working knowledge of how services integrate for governed access (Lake Formation with Athena/Glue/Redshift/EMR). Power BI: semantic model/dataset design and governance; ability to align BI layer with enterprise BI architecture principles. Amazon Bedrock: ability to solution GenAI workloads using Agents/Knowledge Bases and implement guardrails for safety. Strong SQL and data modeling (dimensional modeling, marts, analytical patterns). Role Summary We are seeking a hands-on Snowflake Solutions Architect to design and lead modern, scalable data platforms on Snowflake + AWS Analytics services, enable governed analytics through Power BI semantic models, and accelerate GenAI use cases using Amazon Bedrock (Agents/Knowledge Bases/Guardrails). The role will partner with business and engineering teams to define architecture, guide implementation, and ensure security, performance, and cost-efficiency across the data and AI landscape. Key Responsibilities 1) Solution Architecture (Snowflake + AWS Analytics) Own end-to-end architecture for cloud data platforms leveraging Snowflake and AWS-native analytics services (e.g., S3, Glue, Lake Formation, Athena, Redshift, EMR/Kinesis/MSK as applicable). Define target-state patterns for historical + incremental loads, batch/real-time ingestion, and scalable transformations using tools like dbt and orchestration frameworks (e.g., Airflow). Design Lakehouse / Medallion style architectures and integration approaches between AWS data lake and Snowflake analytics marts, including modern table formats (e.g., Iceberg where applicable). Lead architecture reviews, trade-off decisions (performance/cost/security), and ensure solutions meet non-functional requirements. 2) Data Engineering Enablement & Integration Guide teams on building robust ELT/ETL pipelines, metadata management, and data quality controls (audit, reconciliation, balance/control frameworks). Establish best practices for Snowflake performance tuning, query optimization, and workload management. Define ingestion patterns from enterprise sources (e.g., SAP and other systems) into AWS/Snowflake using standard integration approaches 3) Analytics & BI (Power BI) Architect and govern Power BI semantic models/datasets, ensuring consistent metrics ("single version of truth"), strong performance, and reusability. Implement enterprise-grade security for BI (e.g., Row-Level Security (RLS), access controls, dataset governance) aligned with data platform security design. Partner with BI developers and stakeholders to deliver scalable reporting patterns and lifecycle governance (certification, promotion, workspace standards). 4) GenAI Architecture (Amazon Bedrock) Design GenAI solution patterns using Amazon Bedrock, including Agents, Knowledge Bases (RAG), and safe deployment controls using Guardrails. Define agent tool/action patterns (action groups), retrieval grounding strategy, and observability/tracing for production readiness. 5) Security, Governance & Compliance Implement fine-grained access control across the lake/warehouse ecosystem and enforce governance controls for data access and auditability. Define governance integration approaches beyond native capabilities when needed (catalog/lineage tools, stewardship workflows). 6) Stakeholder Leadership & Delivery Lead technical discovery, translate business needs into architecture, and produce design artifacts (HLD/LLD, roadmaps, standards). Mentor engineers, enforce engineering standards, and collaborate across product, platform, security, and operations teams. Required Qualifications (Must Have) Experience 10+ years in data platform / analytics architecture (or equivalent depth in engineering + architecture). Proven architecture experience with Snowflake (warehouse design, data modeling, performance tuning, governance/security). Strong hands-on AWS analytics/data services experience, especially integrating lake + warehouse and enabling governed access.

Senior Data Engineer / Data Engineering Lead Foster City, CA 94404 (onsite) Salary - Market- Based on experience. Full-Time / Direct-Hire Hiring Data Engineering Lead with strong expertise in Databricks on AWS, MDM, and enterprise data integration. Lead the design and delivery of modern data platforms that enable trusted, governed, and scalable data consumption across business functions. Experience in cloud-based data engineering, middleware integrations, data governance, and enterprise-scale analytics solutions. Work closely with business, architecture, analytics, and engineering teams to drive data modernization initiatives. This role will be instrumental in enabling the enterprise data modernization journey. Establish a scalable and governed data foundation that supports advanced analytics, AI/ML initiatives, and business decision-making. Success in this role will directly improve data quality, consistency, and accessibility across critical business domains. The architecture and integration patterns defined by this role will serve as a foundation for future data and digital transformation programs. Skills / Experience 10+ years of experience in Data Engineering, Data Integration, or Data Platform delivery; hands-on experience with Databricks on AWS; Apache Spark, PySpark, Delta Lake, and Lakehouse architecture Experience designing and implementing enterprise-scale data pipelines; Strong understanding of AWS services such as S3, Glue, Lambda, Redshift, IAM, and CloudWatch Hands-on experience with MDM implementations and integrations; Experience with data quality, data governance, lineage, and master data management processes Strong experience integrating enterprise systems using middleware platforms such as MuleSoft, Boomi, Kafka, or API-based integrations Experience working with structured, semi-structured, and unstructured datasets; Strong SQL and Python development skills Experience with Agile methodologies and DevOps practices; Experience leading distributed teams and managing stakeholder communications Bachelor's Degree or higher in Information Systems, Computer Science, or equivalent experience Skills / Tech Stack Snapshot - Databricks on AWS, Apache Spark, PySpark, Delta Lake, AWS S3, Glue, Lambda, Redshift, MDM Platforms (Informatica MDM, Reltio, Profisee or equivalent), Data Integration & ETL/ELT Frameworks, Middleware Technologies (MuleSoft, Boomi, Kafka, API-led Integrations), Data Warehousing & Data Lake Architecture, Data Governance, MDM, Data Quality & Metadata Management, SQL, Python, Azure DevOps, Jira, Confluence, CI/CD, Agile Delivery Job / Role Description Lead the design and implementation of Databricks-based data platforms on AWS; Architect scalable Lakehouse solutions supporting enterprise analytics workloads Design and develop complex ETL/ELT pipelines using Databricks, Spark, and Cloud-native services; Drive MDM strategy, implementation, and integration across business applications and data platforms Define data integration patterns using APIs, middleware, event-driven architectures, and messaging frameworks; Establish data governance, metadata management, and data quality frameworks Collaborate with business stakeholders to understand data requirements and translate them into technical solutions; Optimize data processing performance, scalability, and operational monitoring Define CI/CD processes and deployment standards for data engineering assets; Mentor engineering teams and provide technical leadership throughout the project lifecycle Support architecture reviews, solution design discussions, and technical decision-making; Ensure compliance with organizational standards, security requirements, and best practices Facilitate architecture reviews, workshops, and stakeholder discussions; Ability to communicate complex technical concepts to business and executive stakeholders; Stakeholder Management - Build strong relationships with business, IT, and external partners; Manage competing priorities and drive consensus among stakeholders; Demonstrate customer-centric and consultative engagement skills. Leadership Skills - Lead cross-functional and geographically distributed teams; Mentor and guide engineers and junior architects; Influence technical decisions through collaboration Problem Solving & Analytical Thinking - Identify root causes of complex data and integration challenges; Evaluate multiple solution options and recommend optimal approaches; Strong troubleshooting and performance optimization capabilities Secondary Skills / Good to have Experience with Snowflake or Microsoft Fabric; Exposure to AI/ML enablement using Databricks ML or AWS SageMaker Experience with Unity Catalog and data governance frameworks; Data Mesh and Data Product concepts. Experience with real-time streaming using Kafka or Kinesis; Informatica IDMC, Talend, or Azure Data Factory. Knowledge of healthcare, life sciences, retail, manufacturing, or financial services domains. Exposure to GenAI and enterprise AI adoption initiatives What Success Looks Like / Expected Outcome Successfully deliver enterprise-scale Databricks capabilities; Establish a governed and scalable Lakehouse architecture for analytics and reporting. Improve master data consistency and data quality across key business domains; Implement standardized integration frameworks and reusable patterns. Establish engineering best practices, automation, and governance processes; Become a trusted advisor for data platform and integration strategy. Enable reliable and efficient data movement across multiple enterprise systems; Achieve stakeholder confidence through consistent delivery and technical leadership

Position:IT Architect - Data & Snowflake Location: Richmond, VA Duration: 12 months Job ID: 175582 Job Overview: The Senior Software Systems Engineer will serve as a strategic technical leader within the Enterprise Data & Analytics team. This role is responsible for defining the architecture, standards, best practices, and future direction of the enterprise data platform. The position involves designing scalable data pipelines, governing Snowflake usage across the organization, and developing high-quality data models that power analytics, BI, AI/ML, and data-driven decision-making. The engineer will ensure the data ecosystem is secure, governed, cost-optimized, and capable of supporting enterprise self-service analytics, operational reporting, and advanced analytics initiatives. Responsibilities: Serve as the technical authority for ETL and data engineering architecture. Design and own end-to-end ETL/ELT architectures for batch and incremental data processing. Architect high-volume, high-throughput pipelines supporting structured and semi-structured data. Define architectural standards, including database design, warehouse sizing, multi-cluster strategies, RBAC, and performance optimization. Establish data engineering, modeling, and transformation standards across the analytics ecosystem. Collaborate with BI and analytics teams to design scalable, governed data models supporting dashboards, KPIs, and advanced analytics. Partner with data engineering, analytics, business SMEs, cloud infrastructure, and cybersecurity teams to design reliable and secure data architectures. Ensure data solutions meet enterprise requirements for reliability, performance, scalability, and disaster recovery. Lead root cause analysis for data platform issues and drive remediation of architectural gaps. Qualifications: 7+ years of experience in data architecture, data engineering, or enterprise data platform roles. Hands-on advanced experience with Snowflake, Oracle Exadata, including performance tuning, RBAC, resource management, and advanced Snowflake features (streams, tasks, data sharing). Strong proficiency with SQL, ELT/ETL frameworks, and cloud data services (Azure/AWS). Expertise in designing analytical data models (Star/Snowflake schemas, data vault, semantic layers). Experience building scalable data pipelines using tools like dbt, Airflow, ADF, Databricks, Informatica, Talend, or similar. Experience with Dataiku for analytics and ML pipeline enablement. Strong communication skills, both verbal and written. Ability to lead, collaborate, or work effectively in a variety of teams, including multi-disciplinary teams. Minimum of a High School Diploma or Equivalency. Preferred Skills: Cloud or platform certifications (Snowflake, Databricks, Azure, Informatica). About PTR Global: PTR Global is a leading provider of information technology and workforce solutions. PTR Global has become one of the largest providers in its industry, with over 5000 professionals providing services across the U.S. and Canada. For more information visit At PTR Global, we understand the importance of your privacy and security. We NEVER ASK job applicants to: Pay any fee to be considered for, submitted to, or selected for any opportunity. Purchase any product, service, or gift cards from us or for us as part of an application, interview, or selection process. Provide sensitive financial information such as credit card numbers or banking information. Successfully placed or hired candidates would only be asked for banking details after accepting an offer from us during our official onboarding processes as part of payroll setup. Pay Range: $72 - $75/hr. W2 The specific compensation for this position will be determined by several factors, including the scope, complexity, and location of the role, as well as the cost of labor in the market; the skills, education, training, credentials, and experience of the candidate; and other conditions of employment. Our full-time consultants have access to benefits, including medical, dental, vision, and 401K contributions, as well as PTO, sick leave, and other benefits mandated by applicable state or localities where you reside or work. If you receive a suspicious message, email, or phone call claiming to be from PTR Global do not respond or click on any links. Instead, contact us directly at +1 . To report any concerns, please email us at

Credit Acceptance is proud to be an award-winning company recognized both locally and nationally across multiple workplace categories. Our world-class culture is shaped by dedicated team members who are driven to succeed as professionals individually and together as a team. Backed by a strong product, exceptional people, and a stable financial foundation, we've grown into a leading provider of used and new car financing across the country. Our Engineering and Analytics Team Members utilize the latest technology to develop, monitor, and maintain complex practices that help optimize our success. Our Team Members value being challenged, are encouraged to express their ideas, and have the flexibility to enjoy work life balance. We build intrinsic value by partnering with all functions of our business to support their success and make strategic business decisions. We focus on professional development and continuous improvement while enjoying a casual work environment and Great Place to Work culture! We are seeking a highly motivated and experienced Leader of ML and AI Engineering within the AI team. The ideal candidate will have a strong technical background in decision science, machine learning, and generative AI with a proven track record in solving business problems and implementing large-scale automated solutions in partnership with the respective engineering teams. The leader will partner with business and engineering stakeholders to formulate the vision to achieve the company's strategic goals and co-lead the roadmap to deliver innovative solutions for dealers, consumers, and team members. As a Senior Manager, MLE at Credit Acceptance, you will play a pivotal role in the success of this mission as you will lead the development of AI-powered solutions across different business areas. This involves understanding the business processes, identifying new opportunities to add value using ML/AI algorithms, and harnessing data sources to build state-of-the-art ML/AI solutions. Outcomes and Activities: This position will work from home; occasional planned travel to an assigned Southfield, Michigan office location may be required. However, this position is permitted to work at a Southfield, Michigan office location if requested by the team member Lead the vision and the strategic execution with a strong focus on continuous and long-term value creation across all participants of our flywheel Collaborate with management and stakeholders to define strategic roadmaps and translate them into actionable quarterly plans. Drive execution and delivery of ML/AI solutions by managing priorities, deadlines, and deliverables, leveraging your technical expertise. Design and deliver scalable, secure systems using state-of-the-art AI/ML technologies and industry best practices, and nurture the culture of creating high-quality, well-tested systems to address critical product and business needs. Troubleshoot and resolve complex technical issues to improve system reliability, scalability, and operational efficiency. Ensure the security, scalability, and architectural integrity of feature designs through reviews across teams. Deliver hands-on solutions while mentoring other data professionals (including MLEs) within the organization Explore and apply advanced machine learning techniques, including large language models (LLMs), deep learning, and graph neural networks, to solve complex challenges across the organization. Guide a team of MLEs across different areas: Mentoring: Mentor team members on design principles, coding standards, and the adoption of AI productivity tools. Recommendations - Personalize guidance across different surfaces using deep learning methods; personalize layouts with Bayesian contextual multi-armed bandits Growth: Foster long-term growth through data-driven causality and incrementality Gen-AI: Power existing applications with Gen AI models and engineering to improve downstream experience and decisions Lifecycle - Using ML models (such as XGBoost & Causal Meta-Learner-based model, etc), proactively guide business teams across different areas Engineering - With engineering partners, build ML and Gen-AI platform and inference pipelines for different types of models Competencies: The following items detail how you will be successful in this role. Customer Empathy: Customer Empathy is the ability to understand the perspectives, pain points, and experiences of customers. It involves actively putting oneself in the customer's shoes, comprehending their needs and challenges, and using that understanding to provide a better, more customer-centric experience. Engineering Excellence: Engineering Excellence is about bringing great craftsmanship and thought leadership to deliver an outstanding product that delights customers and solves for the business. This involves the pursuit and achievement of high standards, best practices, innovation, and superior solutions. One Team: A One Team mindset refers to a collaborative approach across the organization, where individuals work together seamlessly, without boundaries, as a single, cohesive team. Shared goals, open communication and mutual support create a sense of collective purpose. This enables teams to navigate challenges and pursue shared objectives more effectively. Owner's Mindset: Owner's Mindset involves adopting a set of behaviors that reflect a sense of responsibility, accountability, strategic thinking, and a proactive approach to managing your domain. As an owner, you understand the business and your domain(s) deeply and solve for the right outcome for the domain(s) and the business. Requirements: PhD in Computer Science, Stats, Economics, or a relevant technical field with at least 8+ years of relevant experience or MS with at least 10+ years of experience in machine learning and software engineering 8+ years of hands-on experience designing, building and deploying AI (ML, DL, Gen-AI) models, including Reinforcement Learning algorithms, Recommendation systems, Transformers, fine-tuned LLMs, Regressions, etc., with a solid understanding of mathematics, statistics, and engineering needed to build such infrastructure Hands-on expertise in scaling and maintaining production-grade ML services, with a strong focus on ML/LLM Operations (versioning, automation, observability, automated training and monitoring, etc.) and ability to balance ML model complexity with production requirements Passion for identifying new business opportunities and experience of using a test and learn approach to bring scalable and efficient solutions integrating AI algorithms, ML/LLM Ops, and s/w engineering Experience partnering with the engineering, product, business operations, legal and other teams while designing, building, and executing solutions Strong problem-solving skills with bias for action Preferred Experience in automative industry, especially in building ML/AI systems while ensuring local and central regulations Experience in model interpretability and responsible AI practices. Expertise in data science, advanced experimentation and visualization techniques. Experience in designing and implementing pipelines using DAGs (e.g., Kubeflow, DVC, Ray) Ability to construct batch and streaming microservices exposed as gRPC and/or GraphQL endpoints Experience with Databricks MLflow for ML lifecycle management and model versioning Hands-on experience with Databricks Model Serving for production ML deployments Proficiency with GenAI frameworks/tools and technologies such as Apache Airflow, Spark, Flink, Kafka/Kinesis, Snowflake, and Databricks. Demonstrable experience in parameter-efficient fine-tuning, model quantization, and quantization-aware fine-tuning of LLM models Hands-on knowledge of Chain-of-Thoughts, Tree-of-Thoughts, Graph-of-Thoughts prompting strategies Target Compensation: A competitive base salary range from $184,354 - $270,386. This position is eligible for an annual variable bonus of cash and equity, between 15-30%. Bonus amounts are based on individual performance. Final compensation within the range is influenced by many factors including role-specific skills, depth and experience level, industry background, relevant education and certifications. Candidates who reside in the following major metropolitan areas may be eligible for a premium on top of the posted range based on their specific zone: San Francisco, Seattle, Boston, New York City, Los Angeles and San Diego. Benefits Excellent benefits package that includes 401(K) match, adoption assistance, parental leave, tuition reimbursement, comprehensive medical/ dental/vision and many nonstandard benefits that make us a Great Place to Work Our Company Values: To be successful in this role, Team Members need to be: Positive by maintaining resiliency and focusing on solutions Respectful by collaborating and actively listening Insightful by cultivating innovation, accumulating business and role specific knowledge, demonstrating self-awareness and making quality decisions Direct by effectively communicating and conveying courage Earnest by taking accountability, applying feedback and effectively planning and priority setting To create an environment where people do their best work, we focus on the dimensions of Organizational Health. All leaders must: Identify the Right People by recognizing top talent Set Clear Expectations by managing change and directing others Train team members and focus on developing talent Performance Manage by ensuring accountability and driving results Create the Right Environment by establishing trust and managing conflict Maintain the Right Number of team members needed to build an effective team Expectations: Remain compliant with our policies processes and legal guidelines All other duties as assigned Attendance as required by department Advice . click apply for full job details

Job Title: Senior Hadoop Platform Engineer / Hadoop Administrator (SME) Location: Plano, TX / CHARLOTTE, NC Duration: Contract - 12 months Pay Range: $70.22/hr (W2) Job ID: 407333 About BCforward BCforward is a leading global IT consulting and workforce solutions firm providing services and support to Fortune 500 and government clients. Founded in 1998, BCforward has grown with our customers needs into a full-service business solutions provider. With delivery centers and offices across North America and India, we take pride in building long-term relationships and delivering excellence through innovation, collaboration, and integrity. Job Description We are seeking a Hadoop Engineer (SME) to join our dynamic team. The ideal candidate will have strong experience in Cloudera-based Hadoop ecosystem administration, big data platform operations, and DevOps automation and a proven ability to design, operate, and optimize large-scale, secure data platforms supporting analytics and AI/ML workloads. Responsibilities: Own end-to-end operations of Cloudera Hadoop and related data platforms across environments, including upgrades, patches, and deployments. Manage and administer clusters and services for Hadoop, Spark, Kafka, Hive, Impala, HBase, YARN, Zookeeper, SOLR, Hue, and Postgres. Implement authentication, security, and governance including AD/Kerberos, Sentry/Ranger, and auditing. Set up and tune optimal cluster configurations for performance, resiliency, and cost efficiency. Build monitoring, alerting, metrics, capacity forecasting, and disaster recovery procedures. Lead incident, problem, and change management, including root-cause analysis and remediation. Automate platform operations using Ansible, Jenkins, and scripting for CI/CD and configuration management. Integrate data platforms with adjacent applications, containers, and orchestration such as Docker and OpenShift. Analyze and troubleshoot Hadoop ecosystem logs, jobs, and data formats including compression and encoding. Partner with clients, developers, vendors, and project managers to deliver solutions that meet business needs. Required Skills & Qualifications: Expert-level Cloudera Hadoop administration including HDFS, YARN, Hive, Impala, HBase, Kafka, Zookeeper, SOLR, Hue, and Postgres. Deep knowledge of Hadoop architecture, HDFS internals, and cluster sizing and configuration. Strong security background with AD/Kerberos integration and authorization tooling. Proficiency in Unix/Linux administration and scripting with Shell, Python, and Perl. Experience with Spark, Kafka, Hive, Impala, and troubleshooting YARN and ecosystem services. Hands-on CI/CD and automation using Ansible, Jenkins, SVN, and Bitbucket. Knowledge of databases such as Sybase, SQL Server, and Oracle. Experience with monitoring, alerting, and job scheduling systems. Background operating or integrating with platforms such as Databricks, Snowflake, Talend, ELK, and Jupyter. Experience level: 5+ years in Hadoop administration or big data platform engineering roles. Preferred Skills: Cloudera Administrator or Developer certification. Certifications in Cloud, Docker, and OpenShift technologies. Experience supporting AI/ML and data science workloads and notebooks. Why BCforward? At BCforward, we believe in advancing lives and careers. When you join our team, you gain access to: Competitive compensation and benefits. Opportunities for growth with global clients. A supportive, inclusive culture that values innovation and people. Exposure to cutting-edge technologies and projects. About Our Commitment BCforward is an equal opportunity employer. We value diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, or veteran status. Interested? Apply Now! If this sounds like the right opportunity for you, please apply with your most recent resume.

Position: Data Engineer- AWS Location: Jersey City, New Jersey Duration: Contract Job ID: 172543 Job Overview: As a Data Engineer III specializing in Python, Spark, and Data Lake technologies within the Consumer and Community Bank, you will be a key member of an agile team. Your role will involve designing and delivering reliable data collection, storage, access, and analytics solutions that are secure, stable, and scalable. You will develop, test, and maintain essential data pipelines and architectures across diverse technical areas, supporting various business functions to achieve organizational objectives. Responsibilities: Review and ensure sufficient protection of enterprise data through controls. Make custom configuration changes in tools to meet business or customer requests. Update logical or physical data models based on new use cases. Utilize SQL frequently and understand NoSQL databases and their applications. Contribute to a team culture of diversity, opportunity, inclusion, and respect. Develop enterprise data models and maintain large-scale data processing pipelines. Lead code reviews and provide mentoring to team members. Drive data quality and ensure data accessibility for analysts and data scientists. Ensure compliance with data governance requirements and alignment with business goals. Qualifications: Formal training or certification in data engineering concepts with 2+ years of applied experience. Experience across the data lifecycle with advanced SQL skills and understanding of NoSQL databases. Proficiency in statistical data analysis and determining appropriate tools and data patterns. Extensive experience in AWS and maintaining data pipelines using Python and PySpark. Proficient in Python and PySpark for writing and executing complex queries. Proven experience in performance tuning to optimize job execution. Advanced proficiency in leveraging Gen AI models using APIs/SDKs. Expertise in cloud data lakehouse platforms such as AWS Data Lake, Databricks, or Hadoop. Proficiency in relational data stores like Postgres, Oracle, or similar, and NoSQL data stores like Cassandra, DynamoDB, or MongoDB. Advanced proficiency in Cloud Data Warehouses such as Snowflake or AWS Redshift. Experience with scheduling/orchestration tools like Airflow or AWS Step Functions. Proficiency in Unix scripting, data structures, and data serialization formats like JSON, AVRO, or Protobuf. Knowledge of big-data storage formats such as Parquet or Iceberg. Familiarity with data processing methodologies like batch, micro-batching, or streaming. Experience with data modeling techniques such as Dimensional, Data Vault, Kimball, or Inmon. Understanding of Agile methodology, TDD/BDD, and CI/CD tools. Preferred Qualifications: Knowledge of data governance and security best practices. Experience in conducting data analysis to support business insights. Strong expertise in Python and Spark. About PTR Global: PTR Global is a leading provider of information technology and workforce solutions. PTR Global has become one of the largest providers in its industry, with over 5000 professionals providing services across the U.S. and Canada. For more information visit At PTR Global, we understand the importance of your privacy and security. We NEVER ASK job applicants to: Pay any fee to be considered for, submitted to, or selected for any opportunity. Purchase any product, service, or gift cards from us or for us as part of an application, interview, or selection process. Provide sensitive financial information such as credit card numbers or banking information. Successfully placed or hired candidates would only be asked for banking details after accepting an offer from us during our official onboarding processes as part of payroll setup. Pay Range: $65 - $70 The specific compensation for this position will be determined by a number of factors, including the scope, complexity and location of the role as well as the cost of labor in the market; the skills, education, training, credentials and experience of the candidate; and other conditions of employment. Our full-time consultants have access to benefits including medical, dental, vision and 401K contributions as well as any other PTO, sick leave, and other benefits mandated by appliable state or localities where you reside or work. If you receive a suspicious message, email, or phone call claiming to be from PTR Global do not respond or click on any links. Instead, contact us directly at +1 . To report any concerns, please email us at

Job Title: Platform Engineer III Location: (Cincinnati, OH) Duration: Contract - 5 months Pay Range: $70/hr - $72/hr (W2) Job ID: 407250 About BCforward BCforward is a leading global IT consulting and workforce solutions firm providing services and support to Fortune 500 and government clients. Founded in 1998, BCforward has grown with our customers needs into a full-service business solutions provider. With delivery centers and offices across North America and India, we take pride in building long-term relationships and delivering excellence through innovation, collaboration, and integrity. Job Description We are seeking a Data Platform Engineer to lead the architectural hardening and enterprise integration of Dataiku within our modern data stack, including Snowflake, DBT, and AWS. This is not a traditional data science role. You will act as the primary architect responsible for building the governance-as-code layer that enables non-technical users to innovate safely. You will bridge the gap between rapid prototyping and production-grade engineering by implementing automated project standards, data quality gates, and secure tokenization patterns. Responsibilities: Platform hardening by designing and implementing Dataiku Project Standards that act as a linter for production readiness across naming, metadata, and security requirements. Governance automation through custom Dataiku plugins and API integrations to enforce Tier 1 and Tier 2 data quality checks and block promotion to production when standards are not met. Secure architecture in partnership with Information Security to integrate Fortanix tokenization and field-level encryption within Dataiku visual recipes and Python workflows. Hybrid integration to build and maintain the promotion path where ad-hoc Dataiku prototypes are hardened and refactored into DBT when needed for enterprise use. Operational excellence by integrating Dataiku monitoring with ServiceNow to automate incident creation for pipeline failures and data quality drift. User enablement as the technical steward for non-technical business units, delivering approved templates and secure data products in the Data Exchange. Required Skills & Qualifications: Expertise with Dataiku DSS, including project standards, plugins, APIs, and automation nodes. Proficiency with Snowflake, DBT, and AWS data services for production data pipelines. Hands-on experience implementing data quality frameworks and promotion workflows. Strong Python skills for Dataiku code recipes, APIs, and integration tasks. Knowledge of security controls, including tokenization and field-level encryption, preferably with Fortanix or similar tools. Experience integrating monitoring and incident management platforms such as ServiceNow. Clear communication and the ability to enable non-technical stakeholders with safe, reusable patterns. 5+ years in data platform engineering or related roles. Preferred Skills: Experience designing governance-as-code frameworks in enterprise environments. Background working with finance or other business functions to operationalize analytics safely. Why BCforward? At BCforward, we believe in advancing lives and careers. When you join our team, you gain access to: Competitive compensation and benefits. Opportunities for growth with global clients. A supportive, inclusive culture that values innovation and people. Exposure to cutting-edge technologies and projects. About Our Commitment BCforward is an equal opportunity employer. We value diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, or veteran status. Interested? Apply Now! If this sounds like the right opportunity for you, please apply with your most recent resume.

Lead Data Engineer We are Lennar Lennar is one of the nation's leading homebuilders, dedicated to making an impact and creating an extraordinary experience for their Homeowners, Communities, and Associates by building quality homes and providing exceptional customer service, giving back to the communities in which we work and live in, and fostering a culture of opportunity and growth for our Associates throughout their career. Lennar has been recognized as a Fortune 500 company and consistently ranked among the top homebuilders in the United States. A Career that Empowers You to Build Your Future The primary mission of the Lead Data Engineer role is to help our business evolve into a data and insights-driven organization. The Lead Data Engineer will provide technical leadership to our Product Team. This is done by helping design and implement our next generation data and analytics platforms and products using Data engineering best practices. The Lead Data Engineer also will implementing engineering solutions along with the team. In addition, this person focuses on empowering and enabling our business users through self-service and automation. The Lead Data Engineer is a key role in operationalizing Lennar's enterprise data fabric. Your Responsibilities on the Team Design, Build, and Operationalize: Formulate production-grade data engineering solutions for Lennar's data and analytics platforms and products. Pipeline Architecture: Architect and implement reliable ETL, ELT, and streaming data ingestion/delivery processes across multiple enterprise sources. Modern Python Development: Develop, maintain, and containerize modular data applications and utility scripts using Python, leveraging modern cloud infrastructure. Scale and Improve Infrastructure: Improve data ingestion architecture, emphasizing data quality, cost-performance, maintainability, and extensibility across storage and compute layers. Enforce Standards and Downstream Integrity: Define and implement engineering standards for the data team (including code modularization, version control, automated testing, and secure CI/CD workflows). Ensure strict guidelines for schema evolution to safeguard downstream analytics from unilateral changes. Platform Observability: Instrument data analytics platforms with robust metrics, alerting, and automated monitoring (SLAs/SLOs) to ensure high availability and data trustworthiness. AI-Driven Productivity: Leverage modern AI-assisted development tools within daily engineering workflows to accelerate code generation, optimize heavy queries, and improve overall delivery speed. AI/ML Integration: Collaborate with data science teams to design and optimize data layers specifically tailored for Generative AI applications, Retrieval-Augmented Generation (RAG), and LLM frameworks. Ecosystem Integration: Wrangle and integrate data from highly disparate production systems to allow data analysts and data scientists to leverage optimized, end-to-end data products. Business Alignment: Gain a deep understanding of core business processes and align technical data development with strategic business objectives. Requirements Core Expertise (8+ years preferred) in: Data Architecture & Enterprise Modeling: Advanced data warehousing concepts, cloud data lakes, and structured multi-layer designs (Bronze, Silver, Gold). Advanced Data Transformations: Designing complex operational pipelines, data cleanup, and robust standardization strategies. Production SDLC & Workflow Best Practices: Rigorous code reviews, end-to-end testing/QA methodologies, and resilient error-handling frameworks. Data Governance & Security: Implementing enterprise-level role-based access controls (RBAC), data compliance, and secure environments. Strong Technical Experience (3+ to 6+ years) with: Advanced Python Development: Writing clean, object-oriented, and production-grade Python code for complex data manipulation, automation, and API communication. AWS Platform & Containerization: Hands-on experience deploying, managing, and scaling containerized data workloads using AWS ECS (Elastic Container Service) and ECR. Core AWS architecture: S3, IAM, Lambda, EC2, CloudWatch, and CloudTrail. AWS Certification is a strong plus. Snowflake Data Cloud: Account administration, optimal virtual warehouse clustering strategies, and budget-optimization. Expert feature implementation: Data Sharing, Time Travel, and Zero-copy cloning. dbt (Data Build Tool): Managing multi-repository dbt projects and configuring dbt Cloud environments. Creating, documenting, and optimizing advanced dbt models and custom macros. AI-Assisted Engineering & Data Tools: Daily proficiency with AI coding assistants (GitHub Copilot, Cursor, or Claude/OpenAI APIs) to maximize development efficiency. Familiarity with cloud-native AI services (e.g., Snowflake Cortex or AWS Bedrock) for embedding LLM capabilities directly inside the data layer. Exposure to frameworks used for AI data preparation (e.g., LangChain, Vector Databases, or text embedding generation). Data Ingestion & Integration: Incremental loading and Change Data Capture (CDC) methods. Extensive experience querying and integrating with complex external REST APIs. Version Control & CI/CD: Advanced Git/GitHub branching strategies, pull request enforcement, and automated deployment pipelines. Familiarity (1+ years of experience) with: Orchestration & Scheduling: Tools like Prefect, Airflow, or similar modern workflow management software. Data Replication: Enterprise tools such as Qlik Replicate. Soft Skills & Collaboration A "Product-First" Mindset: Demonstrated ability to partner directly with business users and stakeholders to gather solution requirements and translate them into technical assets. Collaborative Drive: Ability to work productively across parallel tracks (Software, Devops, Data) to achieve corporate objectives while protecting engineering quality. Technical Curiosity: A sharp mind and willingness to quickly master new technologies, architectures, and changing business domains. Physical & Office/Site Presence Requirements: This is primarily a sedentary office position which requires the incumbent to have the ability to operate computer equipment, speak, hear, bend, stoop, reach, lift, and move and carry up to 25 lbs. Finger dexterity is necessary. Travel up to 10% of the time to Divisions within the Lennar family. Interact well with co-workers. Cross train for position(s) within the team organizational structure from time to time, as required by the Leadership Team. Comply with and implement company policies and procedures. Accept constructive criticism. Strong work ethic. Team player. This description outlines the basic responsibilities and requirements for the position noted. This is not a comprehensive listing of all job duties of the Associates. Duties, responsibilities and activities may change at any time with or without notice. Life at Lennar At Lennar, we are committed to fostering a supportive and enriching environment for our Associates, offering a comprehensive array of benefits designed to enhance their well-being and professional growth. Our Associates have access to robust health insurance plans, including Medical, Dental, and Vision coverage, ensuring their health needs are well taken care of. Our 401(k) Retirement Plan, complete with a $1 for $1 Company Match up to 5%, helps secure their financial future, while Paid Parental Leave and an Associate Assistance Plan provide essential support during life's critical moments. To further support our Associates, we provide an Education Assistance Program and up to $30,000 in Adoption Assistance, underscoring our commitment to their diverse needs and aspirations. From the moment of hire, they can enjoy up to three weeks of vacation annually, alongside generous Holiday, Sick Leave, and Personal Day policies. Additionally, we offer a New Hire Referral Bonus Program, significant Home Purchase Discounts, and unique opportunities such as the Everyone's Included Day. At Lennar, we believe in investing in our Associates, empowering them to thrive both personally and professionally. Lennar Associates will have access to these benefits as outlined by Lennar's policies and applicable plan terms. Visit to view our suite of benefits. Join the fun and follow us on social media to see what's happening at our company, and don't forget to connect with us on Lennar: Overview LinkedIn for the latest job opportunities. Lennar is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws.

Lead Data Engineer We are Lennar Lennar is one of the nation's leading homebuilders, dedicated to making an impact and creating an extraordinary experience for their Homeowners, Communities, and Associates by building quality homes and providing exceptional customer service, giving back to the communities in which we work and live in, and fostering a culture of opportunity and growth for our Associates throughout their career. Lennar has been recognized as a Fortune 500 company and consistently ranked among the top homebuilders in the United States. Join a Company that Empowers you to Build your Future The primary mission of the Lead Data Engineer role is to help our business evolve into a data and insights-driven organization. This position sits in our Enterprise Data and Analytics team, which aims to drive improved business outcomes using insights gleaned from data and analytics, infusing them into Lennar's corporate fabric. The Lead Data Engineer will provide technical leadership to our data platform engineering team. This is done by helping design and implement our next generation data and analytics platforms and products using Data engineering best practices. The Lead Data Engineer also will implementing engineering solutions along with the team. In addition, this person focuses on empowering and enabling our business users through self-service and automation. The Lead Data Engineer is a key role in operationalizing Lennar's enterprise data fabric. A career with purpose. A career built on making dreams come true. A career built on building zero defect homes, cost management, and adherence to schedules. Your Responsibilities on the Team Design, build, and operationalize data engineering solutions for Lennar's data and analytics platforms and products. Architect and implement ETL, ELT and streaming data ingestion data delivery processes across multiple sources. Experience in data modeling, cloud data lake, cloud data warehouse Instrument data analytics platforms with robust metrics and monitoring. Improve data ingestion architecture, emphasizing data quality, maintainability, and extensibility. Support process improvement on the team to enable rapid development of data products. Define and Implement standards and best practices for data analytics team, including code modularization, versioning, testing, automation of CI/CD workflows, code reviews etc. Gain an understanding of core business processes and align data development with business strategy. Wrangle and integrate data from disparate systems to allow data analysts and data scientists to leverage end-to-end data and information. Requirements Technical Requirements Expertise (At least 8+, prefers 12+ years) in: Data Architecture design Data modeling & Data warehousing concepts Data transformations and standardizations ETL processes & strategies Monitoring and error handling SDLC & workflow best practices Code Reviews QA/Testing methodologies Strong experience (At least 3+, prefers 6+ years) with the following technologies and platforms: AWS platform: S3, EC2, EMR, EKS, Glue, Lambda, AppFlow, Cloudwatch etc. AWS certification is big plus Snowflake Data Cloud Account Administration Virtual warehouse strategies Snowflake feature implementation: Data Sharing, Time Travel, and Zero-copy cloning Role-based Access Control strategies Dbt Managing dbt cloud environment Managing multi-repository dbt projects Creating and managing dbt models Creating and leveraging dbt macros Version control & branching strategies (Github a plus) Proficient in languages: SQL, Python Data governance, security, and compliance concepts Data Ingestion Incremental and CDC ingestion methods REST APIs Familiarity (At least 1+ years of experience) with: Orchestration & scheduling tools (Prefect, Airflow is a plus) Qlik Replicate Other Requirements Ability to work collaboratively and productively with other team members to achieve Lennar's objectives. Thirst to help transform Lennar into an insights-driven organization. Demonstrated some experience in all aspects of development including, but not limited to, gathering requirements, development of technical components related to process scope and supporting testing and post implementation support. Ability to work and partner with users and stakeholders to gather solution requirements. Experience working with business users to understand how to optimally deliver insights within their operational workflows & decision-making processes. Ability and willingness to quickly learn new technologies. Ability and willingness to learn about the business, its strategy, objectives, and core business processes. Additional Requirements: • Travel up to 10% of the time to Divisions within the Lennar family. • Interact well with co-workers. • Cross train for position(s) within the team organizational structure from time to time, as required by the Leadership Team. • Comply with and implement company policies and procedures. • Accept constructive criticism. • Strong work ethic. • Team player. Life at Lennar At Lennar, we are committed to fostering a supportive and enriching environment for our Associates, offering a comprehensive array of benefits designed to enhance their well-being and professional growth. Our Associates have access to robust health insurance plans, including Medical, Dental, and Vision coverage, ensuring their health needs are well taken care of. Our 401(k) Retirement Plan, complete with a $1 for $1 Company Match up to 5%, helps secure their financial future, while Paid Parental Leave and an Associate Assistance Plan provide essential support during life's critical moments. To further support our Associates, we provide an Education Assistance Program and up to $30,000 in Adoption Assistance, underscoring our commitment to their diverse needs and aspirations. From the moment of hire, they can enjoy up to three weeks of vacation annually, alongside generous Holiday, Sick Leave, and Personal Day policies. Additionally, we offer a New Hire Referral Bonus Program, significant Home Purchase Discounts, and unique opportunities such as the Everyone's Included Day. At Lennar, we believe in investing in our Associates, empowering them to thrive both personally and professionally. Lennar Associates will have access to these benefits as outlined by Lennar's policies and applicable plan terms. Visit to view our suite of benefits. Join the fun and follow us on social media to see what's happening at our company, and don't forget to connect with us on Lennar: Overview LinkedIn for the latest job opportunities. Lennar is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws.

Genesis10 is currently seeking a Senior ETL Developer for a contract to hire opportunity with a Regional Financial Institution located in Columbus, OH. Compensation: $60.00 - $66.00 per hour, W2, based on qualifications Position Overview: This role is part of a team working to develop solutions enabling the business to leverage data as an asset within an Enterprise Data Warehouse. As a Senior ETL Developer, you will develop, maintain and enhance code while working closely with multiple technology teams across the enterprise. Key technologies include Snowflake, Python/PySpark and DataStage. Key Responsibilities: Translate requirements and data mapping documents to a technical design Develop, enhance and maintain code following best practices and standards Create and execute unit test plans and support regression and system testing efforts Debug and problem solve issues found during testing and/or production Communicate status, issues and blockers with project team Support continuous improvement by identifying and solving opportunities Primary Requirements: Bachelor's degree or military experience in related field (preferably computer science) 3+ years of experience in ETL development in a Data Warehouse Understanding of enterprise data warehousing best practices and standards Solid experience with Python/PySpark, DataStage ETL and SQL development Proven experience in cloud infrastructure projects with hands on migration expertise on public clouds such as AWS and Azure, preferably Snowflake Knowledge of Cybersecurity organization practices, operations, risk management processes, principles, architectural requirements, engineering and threats and vulnerabilities, including incident response methodologies Good communication and interpersonal skills Good organization skills and the ability to work independently as well as with a team Desired Skills: AWS Certified Solutions Architect - Associate, AWS Certified DevOps Engineer - Professional and/or AWS Certified Solutions Architect - Professional Experience in financial services (banking) industry Only candidates available and ready to work directly as Genesis10 employees will be considered for this position. If you have the described qualifications and are interested in this exciting opportunity, please apply! Ranked a Top Staffing Firm in the U.S. by Staffing Industry Analysts for six consecutive years, Genesis10 puts thousands of consultants and employees to work across the United States every year in contract, contract-for-hire, and permanent placement roles. With more than 300 active clients, Genesis10 provides access to many of the Fortune 100 firms and a variety of mid-market organizations across the full spectrum of industry verticals. For contract roles, Genesis10 offers the benefits listed below. If this is a perm-placement opportunity, our recruiter can talk you through the unique benefits offered for that particular client. Benefits of Working with Genesis10: Access to hundreds of clients, most who have been working with Genesis10 for 5-20+ years The opportunity to have a career-home in Genesis10; many of our consultants have been working exclusively with Genesis10 for years Access to an experienced, caring recruiting team (more than 7 years of experience, on average) Behavioral Health Platform Medical, Dental, Vision Health Savings Account Voluntary Hospital Indemnity (Critical Illness & Accident) Voluntary Term Life Insurance 401K Sick Pay (for applicable states/municipalities) Commuter Benefits (Dallas, NYC, SF, and Illinois) For multiple years running, Genesis10 has been recognized as a Top Staffing Firm in the U.S., as a Best Company for Work-Life Balance, as a Best Company for Career Growth, for Diversity, and for Leadership, amongst others. To learn more and to view all of our available career opportunities, please visit us at our website. Genesis10 is an Equal Opportunity Employer. Candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

Job Title: Data Engineer IV Location: Remote, USA Duration: Contract - 12 months Pay Range: $69/hr $71/hr (W2) Job ID: 406789 About BCforward BCforward is a leading global IT consulting and workforce solutions firm providing services and support to Fortune 500 and government clients. Founded in 1998, BCforward has grown with our customers needs into a full-service business solutions provider. With delivery centers and offices across North America and India, we take pride in building long-term relationships and delivering excellence through innovation, collaboration, and integrity. Job Description We are seeking a Data Engineer IV to join our dynamic team supporting client Customer Experience organization. The ideal candidate will have strong experience in building scalable data pipelines, data architectures, and self-service analytics with AI enablement and a proven ability to deliver actionable insights, automate workflows, and improve customer experience outcomes. Responsibilities: Design, develop, integrate, launch, and maintain scalable batch and streaming data pipelines across PSO. Build and optimize ETL/ELT workflows, data models, and data warehouse architectures. Implement data quality frameworks with validation, monitoring, alerting, and lineage tracking. Develop and manage orchestration workflows (e.g., Airflow, Dataswarm) for scheduling and dependencies. Optimize query performance, pipeline efficiency, and storage costs at scale. Create interactive visualizations and self-service dashboards that communicate complex insights. Integrate diverse data sources including customer interactions, feedback, behavioral data, and operational logs. Develop and track KPIs to measure the effectiveness of customer experience initiatives. Enable AI/ML analytics by building feature pipelines, curated datasets, and model-ready assets. Leverage LLMs and generative AI to automate data workflows and accelerate insight generation. Develop prompt engineering frameworks, AI-assisted reporting, and intelligent automation solutions. Partner with engineering and data science to integrate model outputs into dashboards and operations. Evaluate emerging AI tools and techniques to advance analytics and data engineering capabilities. Collaborate with customer service, operations, product, and engineering to drive data-informed decisions. Champion data literacy and AI enablement through documentation, training, and best practices. Required Skills & Qualifications: 8+ years of experience in quantitative and operational analyses within customer support/service, e-commerce, or order management. Proven data engineering skills building production-grade pipelines, data models, and ETL/ELT at scale. Proficiency in SQL and one programming language, preferably Python. Experience with data warehousing platforms such as Hive, Presto, Spark, Snowflake, or BigQuery. Experience with workflow orchestration tools such as Airflow or Dataswarm. Experience creating self-service dashboards with Tableau, Looker, or equivalent. Knowledge of data quality frameworks, data governance, and dimensional data modeling. Hands-on AI/ML enablement experience, including feature pipelines or LLM-based analytics workflows. Ability to manipulate large datasets to generate insights and solutions. Record of operating independently, managing ambiguity, and delivering results. Strong communication skills for technical and non-technical audiences. Cross-functional experience influencing change through data-driven insights. Preferred Skills: Experience with generative AI, including prompt engineering, RAG, LLM APIs, or agent workflows. Familiarity with Git, CI/CD for data pipelines, and infrastructure-as-code. Experience with streaming technologies such as Kafka or Spark Streaming. Knowledge of metadata management, data cataloging, and lineage tools. Background in CX/CS operations and metrics; familiarity with Salesforce. Experience with digital analytics tools such as Google Analytics or Adobe Analytics. Experience scripting automation and internal tooling in Python or Bash. Familiarity with agile development methodologies. Experience in high-volume consumer electronics and operations for customer experience or support. Why BCforward? At BCforward, we believe in advancing lives and careers. When you join our team, you gain access to: Competitive compensation and benefits. Opportunities for growth with global clients. A supportive, inclusive culture that values innovation and people. Exposure to cutting-edge technologies and projects. About Our Commitment BCforward is an equal opportunity employer. We value diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, or veteran status. Interested? Apply Now! If this sounds like the right opportunity for you, please apply with your most recent resume.

The Disney Decision Science and Integration (DDSI) team leverages advanced technologies, data analytics, and scientific approaches such as optimization and statistical modeling to build innovative tools that shape business decisions across The Walt Disney Company. We support Disney Entertainment (ABC, The Walt Disney Studios, Disney+, Hulu), ESPN, Disney Experiences (Theme Parks, Cruise Line, Consumer Products, DVC), and Corporate Finance with strategic applications that enable data-driven decision-making. This team works in office. What You Will Do As the Ontology/Semantic Librarian, you will lead the design, development, and governance of enterprise ontologies, semantic layers, and knowledge graphs that serve as the intelligent backbone for a modern federated data platform. This role combines deep semantic modeling expertise with hands-on implementation of graph technologies, vector databases, and federated data architectures to accelerate business value delivery. This role will make key contributions to the Data Unification initiative by enabling rapid discovery and utilization of our vast data assets across the Disney enterprise. Design and build enterprise ontologies and semantic models that align business objectives with technical implementation, ensuring rapid enablement of business use cases such as unified reporting, AI agents, data marketplaces, and cross-functional insights. Lead the creation and maintenance of semantic layer graphs, knowledge graphs, and entity graphs, clearly distinguishing and leveraging the strengths of each approach. Develop and implement strategies for using vector databases and graph databases (e.g., Neo4j, Amazon Neptune, Qdrant, or similar) to enable powerful LLM-augmented search and reasoning over highly federated, heterogeneous data stores. Partner with data engineering, AI, and business teams to translate business goals into ontological models that drive measurable outcomes. Design and evolve the enterprise Data Catalog with rich semantic metadata, lineage, and governance capabilities. Contribute to the development of a unified data access layer that supports querying across Snowflake, Databricks, PostgreSQL, MongoDB, S3, Kafka, and other sources through a single semantic interface. Implement and enforce enterprise security models (RBAC/ABAC, column/row-level security, and dynamic masking) through the ontology and semantic layer. Collaborate on AI integration initiatives, including building ontology-driven agents, RAG pipelines, and agent-to-agent communication protocols. Establish ontology governance processes, versioning, and lifecycle management to ensure scalability and consistency across the enterprise. Contribute to the internal Data Marketplace by defining semantic data products with clear business value and consumption models. Mentor team members on semantic technologies and best practices for ontology-driven data architecture. Required Qualifications & Skills 7+ years of experience in data engineering, data architecture, semantic technologies, knowledge engineering, or related fields with a strong technical implementation background. Deep expertise in ontology modeling (OWL, RDF, SKOS, SHACL) and graph technologies. Strong understanding of the differences between semantic layer graphs, knowledge graphs, and entity graphs and when to apply each. Hands-on experience with graph databases (Neo4j, Neptune, etc.) and vector databases for semantic search and LLM integration. Proficiency in designing and implementing Data Catalogs and semantic metadata management solutions. Experience building solutions on top of federated data architectures involving relational (PostgreSQL, Snowflake), document (MongoDB), object (S3), and streaming (Kafka) systems. Demonstrated ability to translate complex business goals into ontological designs that accelerate delivery of business value. Strong programming skills, particularly Python, SPARQL, Cypher, GraphQL, and SQL. Experience with modern data platforms, cloud services (AWS preferred), and infrastructure-as-code practices. Solid understanding of data governance, security (RBAC/ABAC, dynamic masking), and compliance in enterprise environments. Excellent communication skills with the ability to bridge business stakeholders and technical teams. Desired Qualifications Experience building ontologies in large, complex enterprises (especially with media, entertainment, hospitality, or consumer-focused businesses). Hands-on experience with Generative AI, LLMs, RAG architectures, and agentic systems. Familiarity with data marketplace or data product platforms. Prior work with Apache Iceberg, Trino/Presto, or similar federated query engines. Knowledge of semantic web standards and tools (Protégé, TopBraid, Stardog, etc.). Background in formal knowledge representation, taxonomy development, or master data management. Required Education Bachelor's degree and/or equivalent work experience Preferred Education Bachelor's degree in Computer Science, Information Systems, Data Science, Philosophy (with logic focus), Linguistics, or a related technical field (or equivalent experience). Master's degree or PhD in a relevant field (Semantic Technologies, AI, Data Science, or Computer Science). The hiring range for this position in Lake Buena Vista, FL is $148,300 to $198,800 per year, in Burbank, CA is $155,700 to $208,700 per year, and New York, NY or Seattle, WA is $163,100 to $218,700 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.

The Disney Decision Science and Integration (DDSI) team leverages advanced technologies, data analytics, and scientific approaches such as optimization and statistical modeling to build innovative tools that shape business decisions across The Walt Disney Company. We support Disney Entertainment (ABC, The Walt Disney Studios, Disney+, Hulu), ESPN, Disney Experiences (Theme Parks, Cruise Line, Consumer Products, DVC), and Corporate Finance with strategic applications that enable data-driven decision-making. This team works in office. What You Will Do As the Ontology/Semantic Librarian, you will lead the design, development, and governance of enterprise ontologies, semantic layers, and knowledge graphs that serve as the intelligent backbone for a modern federated data platform. This role combines deep semantic modeling expertise with hands-on implementation of graph technologies, vector databases, and federated data architectures to accelerate business value delivery. This role will make key contributions to the Data Unification initiative by enabling rapid discovery and utilization of our vast data assets across the Disney enterprise. Design and build enterprise ontologies and semantic models that align business objectives with technical implementation, ensuring rapid enablement of business use cases such as unified reporting, AI agents, data marketplaces, and cross-functional insights. Lead the creation and maintenance of semantic layer graphs, knowledge graphs, and entity graphs, clearly distinguishing and leveraging the strengths of each approach. Develop and implement strategies for using vector databases and graph databases (e.g., Neo4j, Amazon Neptune, Qdrant, or similar) to enable powerful LLM-augmented search and reasoning over highly federated, heterogeneous data stores. Partner with data engineering, AI, and business teams to translate business goals into ontological models that drive measurable outcomes. Design and evolve the enterprise Data Catalog with rich semantic metadata, lineage, and governance capabilities. Contribute to the development of a unified data access layer that supports querying across Snowflake, Databricks, PostgreSQL, MongoDB, S3, Kafka, and other sources through a single semantic interface. Implement and enforce enterprise security models (RBAC/ABAC, column/row-level security, and dynamic masking) through the ontology and semantic layer. Collaborate on AI integration initiatives, including building ontology-driven agents, RAG pipelines, and agent-to-agent communication protocols. Establish ontology governance processes, versioning, and lifecycle management to ensure scalability and consistency across the enterprise. Contribute to the internal Data Marketplace by defining semantic data products with clear business value and consumption models. Mentor team members on semantic technologies and best practices for ontology-driven data architecture. Required Qualifications & Skills 7+ years of experience in data engineering, data architecture, semantic technologies, knowledge engineering, or related fields with a strong technical implementation background. Deep expertise in ontology modeling (OWL, RDF, SKOS, SHACL) and graph technologies. Strong understanding of the differences between semantic layer graphs, knowledge graphs, and entity graphs and when to apply each. Hands-on experience with graph databases (Neo4j, Neptune, etc.) and vector databases for semantic search and LLM integration. Proficiency in designing and implementing Data Catalogs and semantic metadata management solutions. Experience building solutions on top of federated data architectures involving relational (PostgreSQL, Snowflake), document (MongoDB), object (S3), and streaming (Kafka) systems. Demonstrated ability to translate complex business goals into ontological designs that accelerate delivery of business value. Strong programming skills, particularly Python, SPARQL, Cypher, GraphQL, and SQL. Experience with modern data platforms, cloud services (AWS preferred), and infrastructure-as-code practices. Solid understanding of data governance, security (RBAC/ABAC, dynamic masking), and compliance in enterprise environments. Excellent communication skills with the ability to bridge business stakeholders and technical teams. Desired Qualifications Experience building ontologies in large, complex enterprises (especially with media, entertainment, hospitality, or consumer-focused businesses). Hands-on experience with Generative AI, LLMs, RAG architectures, and agentic systems. Familiarity with data marketplace or data product platforms. Prior work with Apache Iceberg, Trino/Presto, or similar federated query engines. Knowledge of semantic web standards and tools (Protégé, TopBraid, Stardog, etc.). Background in formal knowledge representation, taxonomy development, or master data management. Required Education Bachelor's degree and/or equivalent work experience Preferred Education Bachelor's degree in Computer Science, Information Systems, Data Science, Philosophy (with logic focus), Linguistics, or a related technical field (or equivalent experience). Master's degree or PhD in a relevant field (Semantic Technologies, AI, Data Science, or Computer Science). The hiring range for this position in Lake Buena Vista, FL is $148,300 to $198,800 per year, in Burbank, CA is $155,700 to $208,700 per year, and New York, NY or Seattle, WA is $163,100 to $218,700 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.

Disney Entertainment and ESPN Product & Technology Technology is at the heart of Disney's past, present, and future. Disney Entertainment and ESPN Product & Technology is a global organization of engineers, product developers, designers, technologists, data scientists, and more - all working to build and advance the technological backbone for Disney's media business globally. The team marries technology with creativity to build world-class products, enhance storytelling, and drive velocity, innovation, and scalability for our businesses. We are Storytellers and Innovators. Creators and Builders. Entertainers and Engineers. We work with every part of The Walt Disney Company's media portfolio to advance the technological foundation and consumer media touch points serving millions of people around the world. Here are a few reasons why we think you'd love working here: Building the future of Disney's media: Our Technologists are designing and building the products and platforms that will power our media, advertising, and distribution businesses for years to come. Reach, Scale & Impact: More than ever, Disney's technology and products serve as a signature doorway for fans' connections with the company's brands and stories. Disney+. Hulu. ESPN. ABC. ABC News and many more. These products and brands - and the unmatched stories, storytellers, and events they carry - matter to millions of people globally. Innovation: We develop and implement groundbreaking products and techniques that shape industry norms, and solve complex and distinctive technical problems. Ad Platforms is responsible for Disney's industry-leading ad technology and products - driving advertising performance, innovation, and value in Disney's sports, news, and entertainment content, across all media platforms. Job Summary: As a Software Engineer, you will use your deep Salesforce CRM Analytics, scripting, DevOps, and data persistence skills to write and test code that delivers new features for our application portfolio. You will be an important part of a motivated team where we'll be looking for you to be a key contributor to collaborate on application architecture, code quality, and make sure we are building the right things for our users. We want someone that has grown up through the software development ranks - possessing 3 or more years' experience in designing and architecting highly scalable, secure, performant, and usable web applications using Salesforce and CRM Analytics. The ideal candidate would possess skills in Salesforce technology while having experience with cloud platforms (AWS, Azure or GCP), coupled with hands on persistence and data streaming technology experience (Snowflake, Kafka). Experience with Python and Databricks is highly desirable. We would like you to be comfortable performing multiple roles. We strive to get things done quickly, with high quality, and we are committed to the agile methodology. Our work is guided by lean principles (looking at value and looking for waste; not doing anything 'for the sake of doing it'). We're looking for a passionate, impactful, engineer who wants to come here to do their very best work and make their mark, add their chapter to the long and storied history of The Walt Disney Company. Someone who holds themselves and their teammates accountable in a professional, collaborative manner. A collaborative technologist who seeks to bring the best out in themselves and those around them. Someone who can provide a fresh perspective and innovative insight to our initiatives. Responsibilities and Duties of the Role: KEY RESPONSIBILITIES Deliver software projects with high quality on time. Provide domain expertise and innovative solutions to complex business problems Collaborate with leads and contribute to software architectures which are robust, scalable, fault-tolerant, secured and cloud-native Possess Salesforce CRM Analytics solution design and implementation experience Reason logically and creatively, identifying problems, drawing valid conclusions from the data available, and develop effective solutions while applying creative thinking in the design and development of high performing web applications Stay up-to-date on the latest software development technologies and trends Contribute to code reviews and ensure that all code meets quality standards Deliver multiple projects utilizing an Agile methodology Take a high ownership, self-sufficient, hands-on position on the team to contribute and drive quality, maintain application stability Write complex programs, analyze code changes and suggest improvements Check-in valuable, clean and well-documented code on a daily basis that adds new features and capabilities Investigate and resolve any production issues from end user (UI) to persistence layer and work to prevent them Work with the team to make sure all project deliverables are on time and high quality Work collaboratively with cross-functional teams to ensure that software solutions align with business goals Required Education, Experience/Skills/Training: YOU MUST Hold a Bachelor's degree in Computer Science, Computer Information Systems, Engineering, or another technical field Have 3+ years of experience in web application development or software engineering in a large enterprise environment using Salesforce and CRM Analytics platform Have Salesforce Certifications Be able to demonstrate significant experience working with relational databases, SQL and newer NoSQL data stores as well as event streaming platforms (Snowflake, Kafka) Have a strong interest in open source technology Possess good communication skills and enjoy mentoring and helping others to succeed as a team Care about your craft and have opinions about the "right" way to do things with technology PREFERRED EXPERIENCE/EDUCATION/SKILLS Master's degree in Computer Science, Software Engineering or related technical discipline is highly desirable Experience in vibe coding and AI tools Previous work experience in Ad Platforms, Accounts Receivable and/or financial applications Experience working with vendor teams to deliver high quality results Knowledge of AWS managed services, performance testing and application profiling Strong curiosity about how Disney delivers the Magic and a desire to be a part of it The hiring range for this position in New York, NY is between $120,300 - $161,300 and Seattle, WA is between $120,300 - $161,300. The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.

The Disney Decision Science and Integration (DDSI) team leverages advanced technologies, data analytics, and scientific approaches such as optimization and statistical modeling to build innovative tools that shape business decisions across The Walt Disney Company. We support Disney Entertainment (ABC, The Walt Disney Studios, Disney+, Hulu), ESPN, Disney Experiences (Theme Parks, Cruise Line, Consumer Products, DVC), and Corporate Finance with strategic applications that enable data-driven decision-making. This team works in office. What You Will Do As the Ontology/Semantic Librarian, you will lead the design, development, and governance of enterprise ontologies, semantic layers, and knowledge graphs that serve as the intelligent backbone for a modern federated data platform. This role combines deep semantic modeling expertise with hands-on implementation of graph technologies, vector databases, and federated data architectures to accelerate business value delivery. This role will make key contributions to the Data Unification initiative by enabling rapid discovery and utilization of our vast data assets across the Disney enterprise. Design and build enterprise ontologies and semantic models that align business objectives with technical implementation, ensuring rapid enablement of business use cases such as unified reporting, AI agents, data marketplaces, and cross-functional insights. Lead the creation and maintenance of semantic layer graphs, knowledge graphs, and entity graphs, clearly distinguishing and leveraging the strengths of each approach. Develop and implement strategies for using vector databases and graph databases (e.g., Neo4j, Amazon Neptune, Qdrant, or similar) to enable powerful LLM-augmented search and reasoning over highly federated, heterogeneous data stores. Partner with data engineering, AI, and business teams to translate business goals into ontological models that drive measurable outcomes. Design and evolve the enterprise Data Catalog with rich semantic metadata, lineage, and governance capabilities. Contribute to the development of a unified data access layer that supports querying across Snowflake, Databricks, PostgreSQL, MongoDB, S3, Kafka, and other sources through a single semantic interface. Implement and enforce enterprise security models (RBAC/ABAC, column/row-level security, and dynamic masking) through the ontology and semantic layer. Collaborate on AI integration initiatives, including building ontology-driven agents, RAG pipelines, and agent-to-agent communication protocols. Establish ontology governance processes, versioning, and lifecycle management to ensure scalability and consistency across the enterprise. Contribute to the internal Data Marketplace by defining semantic data products with clear business value and consumption models. Mentor team members on semantic technologies and best practices for ontology-driven data architecture. Required Qualifications & Skills 7+ years of experience in data engineering, data architecture, semantic technologies, knowledge engineering, or related fields with a strong technical implementation background. Deep expertise in ontology modeling (OWL, RDF, SKOS, SHACL) and graph technologies. Strong understanding of the differences between semantic layer graphs, knowledge graphs, and entity graphs and when to apply each. Hands-on experience with graph databases (Neo4j, Neptune, etc.) and vector databases for semantic search and LLM integration. Proficiency in designing and implementing Data Catalogs and semantic metadata management solutions. Experience building solutions on top of federated data architectures involving relational (PostgreSQL, Snowflake), document (MongoDB), object (S3), and streaming (Kafka) systems. Demonstrated ability to translate complex business goals into ontological designs that accelerate delivery of business value. Strong programming skills, particularly Python, SPARQL, Cypher, GraphQL, and SQL. Experience with modern data platforms, cloud services (AWS preferred), and infrastructure-as-code practices. Solid understanding of data governance, security (RBAC/ABAC, dynamic masking), and compliance in enterprise environments. Excellent communication skills with the ability to bridge business stakeholders and technical teams. Desired Qualifications Experience building ontologies in large, complex enterprises (especially with media, entertainment, hospitality, or consumer-focused businesses). Hands-on experience with Generative AI, LLMs, RAG architectures, and agentic systems. Familiarity with data marketplace or data product platforms. Prior work with Apache Iceberg, Trino/Presto, or similar federated query engines. Knowledge of semantic web standards and tools (Protégé, TopBraid, Stardog, etc.). Background in formal knowledge representation, taxonomy development, or master data management. Required Education Bachelor's degree and/or equivalent work experience Preferred Education Bachelor's degree in Computer Science, Information Systems, Data Science, Philosophy (with logic focus), Linguistics, or a related technical field (or equivalent experience). Master's degree or PhD in a relevant field (Semantic Technologies, AI, Data Science, or Computer Science). The hiring range for this position in Lake Buena Vista, FL is $148,300 to $198,800 per year, in Burbank, CA is $155,700 to $208,700 per year, and New York, NY or Seattle, WA is $163,100 to $218,700 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.

Department Description At Disney, we're storytellers. We make the impossible, possible. The Walt Disney Company is a world-class entertainment and technological leader. Walt's passion was to continuously envision new ways to move audiences around the world-a passion that remains our touchstone in an enterprise that stretches from theme parks, resorts and a cruise line to sports, news, movies and a variety of other businesses. Uniting each endeavor is a commitment to creating and delivering unforgettable experiences - and we're constantly looking for new ways to enhance these exciting experiences. The Enterprise Technology mission is to deliver technology solutions that align to business strategies while enabling enterprise efficiency and promoting cross-company collaborative innovation. Our group drives competitive advantage by enhancing our consumer experiences, enabling business growth, and advancing operational excellence. Team Description: The Data Solutions & Products group is part of Enterprise Technology. We are responsible for designing and developing enterprise solutions and managing a diverse portfolio of products and tools related to Data, Analytics and Automation used by business teams across The Walt Disney Company. The Lead Data Platform Engineer position is one of the key technical leadership roles on the team. You will have the opportunity to be the Lead Engineer for major development projects related to data & analytics solutions and platforms. The first project this role will be responsible as the Lead Engineer for leading is the implementation of a Finance Data Layer-a data lakehouse that provides data to Finance systems and applications including an EPM system, BI reporting & analytics, and AI/ML applications. You will be working in a challenging, fast-paced, highly collaborative and rewarding environment, as a member of product and project teams that work closely with each other and with our business partners to deliver innovative and industry-leading business solutions. What You'll Do: Leading teams of developers (both Disney Cast Members and external vendors) in major software/data development projects. Designing and developing highly scalable, distributed enterprise data platform solutions. Design, develop and implement scalable distributed enterprise data platform solutions, focusing on multi-cluster warehousing, data sharing, and optimized storage. Write code that establishes and enhances frameworks and design proof of concepts, and review code for correctness, and its impact on software architecture. Lead the development of high-performance ETL/ELT pipelines using tools like dbt, Python, Airflow and more to integrate diverse data sources. Provide mentorship and direction to more junior software engineers on the team; serve as an advanced resources for other engineers on the team. Being the ongoing technical lead for data platform products (post-implementation)-leading engineering support for the production platform, leading ongoing enhancement projects, guiding technical product roadmap Partner with Data Science, Analytics, and Product teams to ensure the platform meets evolving business requirements. Establish standards for data modeling (Vault, Star Schema), security (RBAC), and data quality frameworks. Excellent communication skills, ability to communicate well to both technical and business audiences Strong collaboration skills Required Qualifications & Skills: 7+ years of professional programming and design experience in Scala, Java, Python etc.; demonstrated experience designing and developing enterprise data solutions and platforms Demonstrated experience leading engineering initiatives on major software and data development projects Experience with medallion-based data Lakehouse architectures Experience with high-scale cloud data platforms and with at least one major cloud provider (AWS, Azure, or GCP) Expert knowledge of data integration, dimensional modeling and data warehousing techniques. Experience implementing CI/CD pipelines for data Proficiency in Java, SQL Experience with Snowflake Preferred Qualifications: Experience with enterprise data domains is preferred (especially Finance and HR data) Experience with AI/ML Experience with SAP Systems (S4, BW, HANA, BDC) Experience with EPM Systems (e.g. Oracle EPM) Experience with Data Governance Experience with Master Data Management Experience with BI tools Required Education: Bachelor's degree in computer science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience Master's Degree a Plus The hiring range for this position in Burbank, CA is $155,700 - $208,700 per year and in Seattle, WA is $163,100 - $218,700 per year and in Orlando, FL is $148,300 - $190,200 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.