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This job is with Allianz Commercial, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. We are looking for an experienced Principal Data Engineer to work hands-on on the re-engineering of an existing enterprise data platform built on Azure Synapse Analytics. The role requires strong technical depth to audit, understand, and validate a complex end-to-end data architecture spanning source ingestion through to consumption - and to help deliver the migration of validated workloads to Databricks. This is hands on role and demands the ability to reverse-engineer existing implementations, assess their correctness, and build to an agreed migration strategy. Key Responsibilities Contribute to the technical assessment and re-engineering of an existing enterprise data platform, spanning all layers from source ingestion through to data consumption Reverse-engineer, document, and validate existing pipeline logic, data models, transformation frameworks, and data governance controls Identify gaps, defects, and technical debt across the platform and remediate where implementations are incorrect or sub-optimal Ensure correctness of data processing patterns including change data capture, slowly changing dimensions, deduplication, and business reconciliation Implement target-state designs aligned to modern lakehouse principles, ensuring feature parity and business logic fidelity during transitions Support platform evolution initiatives, including parallel-run phases where multiple implementations operate simultaneously, validating output consistency before cutover Execute migration of existing workloads to modern data platforms, preserving existing governance and control framework semantics Re-implement ingestion, transformation, and orchestration pipelines on target platforms, maintaining audit, quality, and reconciliation standards Collaborate with business, data governance, and architecture stakeholders to validate embedded business rules and data quality requirements Mentor less experienced engineers, review code and designs, and support decommission planning for legacy components Core Technical Skills Azure Synapse & Data Platform Mandatory hands-on expertise with: Azure Synapse Analytics (Pipelines, Spark Pool, Dedicated SQL Pool) Azure Data Lake Storage Gen2 (ADLS Gen2) Delta Lake on Azure (Synapse Lakehouse patterns) Oracle Golden Gate Replication for real-time source integration Azure Analysis Services and Power BI consumption layer patterns Deep understanding of medallion architecture: Raw / Harmonized / Conformed / Consumption layers Strong knowledge of SCD Type 0/1/2, CDC patterns, soft/hard delete, and retroactive change processing Experience with Synapse SQL Pool - stored procedures, control tables, and data quality validation patterns Experience with audit, balance, and control frameworks - parameterized, modular pipeline governance at enterprise scale Familiarity with config-driven and automation-first pipeline patterns (YAML, PySpark, SQL-driven generation from mapping documents) Databricks & Lakehouse Hands-on experience with Azure Databricks (Delta Live Tables, Unity Catalog preferred) Strong Apache Spark skills (PySpark / Spark SQL) Experience migrating workloads from legacy data warehouse or Synapse environments to a Databricks Lakehouse Ability to re-implement governance and control frameworks natively in Databricks (audit logging, reconciliation, DQ checks) Experience with Delta Lake features: MERGE, CDC, time travel, schema enforcement Data Engineering & Development Strong Python and SQL programming skills Experience with ETL/ELT at scale: denormalization, surrogate keys, directory tables, curated data models Experience integrating complex data sources: Oracle DB, SQL Server, Azure SQL DB, file systems, Salesforce, APIs Strong data modelling skills: relational, dimensional, and lakehouse-oriented DevOps & Automation CI/CD pipelines for data engineering (Azure DevOps / GitHub Actions) Infrastructure as Code (Terraform or ARM) Containerization (Docker) Experience with automated testing frameworks for data pipelines (unit testing, reconciliation-based validation) Nice to Have Experience with Unity Catalog for data governance and lineage Familiarity with Azure Purview for data cataloguing and governance Exposure to real-time and streaming pipelines (Event Hub / Kafka / Kinesis) Experience with GenAI or ML platform integration (MLOps, feature engineering pipelines) Familiarity with monitoring and observability tools (e.g., Dynatrace) Exposure to BI tools (Power BI, Tableau) Experience & Profile 7+ years of hands-on experience in Data Engineering, including platform migration or re-engineering work Proven track record working on existing, complex enterprise data platforms - not just building from scratch Deep knowledge of enterprise data governance patterns: audit trails, reconciliation, data quality controls, SCD versioning Strong analytical mindset: ability to read existing implementations, identify intent versus defect, and make sound re-engineering decisions Primarily hands-on, while comfortable contributing to technical design discussions Strong communication skills - able to engage business, governance, and engineering stakeholders with clarity Experience working in regulated or enterprise-scale environments (financial services a plus) What we offer We offer a hybrid work model which recognizes the value of striking a balance between in-person collaboration and remote working We believe in rewarding performance and our compensation and benefits package includes health insurance, company bonus scheme, 401(K) with company match, company paid holidays, paid time off, paid volunteer days, tuition reimbursement, paid parental leave, an employee shares program and employee discounts From career development and digital learning programs to international career mobility, we offer lifelong learning for our employees worldwide and an environment where innovation, delivery and empowerment are fostered. The annualized base pay range for this role is $110,000 - 150,000. The annual base salary range represents a nationwide market range. The actual salary for this position will be determined by a number of factors, including the scope, complexity and location of the role, and the skills, education, training, credentials and experience of the candidate. The base pay is just one component of the ATA total compensation package. As part of our comprehensive compensation and highly rated benefits programs, ATA also offers eligibility for an incentive-based annual bonus. About Allianz Technology Allianz Group is one of the most trusted insurance and asset management companies in the world. Caring for our employees, their ambitions, dreams and challenges is what makes us a unique employer. We are united by a shared commitment: to put our customers first and at the centre of everything we do. Their needs inspire our thinking and guide our actions. Together, we can build an environment where everyone feels empowered and confident to explore, grow and shape a better future - for our customers and for the world around us. At Allianz, we stand for unity: we believe that a united world is a more prosperous world, and we are dedicated to consistently advocating for equal opportunities for all. The foundation for this is our inclusive workplace, where people and performance both matter, and where integrity, fairness, inclusion and trust are at the heart of our culture. We therefore welcome applications regardless of ethnicity or cultural background, age, gender, nationality, religion, social class, disability or sexual orientation, or any other characteristics protected under applicable local laws and regulations. Join us. Let's care for tomorrow. You.IT

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you. About the Role McKesson is seeking a Senior Product Manager, Finance Systems & ERP Transformation to help modernize and optimize Finance technology capabilities across General Ledger, Accounts Payable, Accounts Receivable, Financial Close, Reporting, and related Finance processes. In this role, you will partner with Finance, Accounting, Decision Intelligence, Technology, and business stakeholders to translate business needs into clear requirements, product priorities, and scalable system solutions. This role is ideal for a finance systems product leader who understands ERP platforms, financial operations, data quality, reporting, controls, and Agile delivery. You will own and prioritize the Finance Systems product backlog, support roadmap planning, and help prepare the organization for future ERP transformation initiatives, including SAP S/4HANA. What You'll Do Serve as a key liaison between Finance stakeholders and technology teams to translate business needs into actionable requirements, user stories, and delivery outcomes. Manage and prioritize the Finance Systems product backlog, including epics, features, acceptance criteria, release readiness, and stakeholder communication. Partner with Finance leaders to evaluate, optimize, and standardize processes across GL, AP, AR, Fixed Assets, Financial Reporting, Budgeting, Forecasting, and Close. Lead requirements gathering, process mapping, gap analysis, solution design, and business case development for Finance systems initiatives. Support ERP transformation readiness, including SAP S/4HANA planning, process alignment, UAT, change management, adoption, and business readiness. Collaborate with engineering, data, analytics, integration, vendor, and platform teams to deliver scalable Finance reporting, data quality, and automation improvements. Define Finance data quality, reconciliation, validation, reporting, lineage, and acceptance criteria to support trusted financial information. Support change control, release governance, SOX-aware requirements, auditability, and operational readiness for Finance system enhancements. Basic Requirements 7+ years of experience in Finance Systems, Business Analysis, Product Management, ERP implementations, Finance transformation, or related roles. Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field, or equivalent practical experience. Experience with Finance processes such as General Ledger, Accounts Payable, Accounts Receivable, Fixed Assets, Financial Reporting, Budgeting, Forecasting, or Financial Close. Experience gathering, documenting, and managing business requirements, process flows, functional specifications, user stories, and acceptance criteria. Experience managing or contributing to product backlogs, roadmap priorities, sprint planning, backlog refinement, UAT, and release readiness. Experience working with ERP platforms such as PeopleSoft Financials, SAP S/4HANA, or comparable enterprise Finance systems. Experience analyzing current-state processes, designing future-state solutions, and driving measurable process improvement. Experience partnering with business stakeholders, technology teams, vendors, and implementation partners to deliver Finance systems enhancements. Preferred Skills/Experience Experience supporting large-scale ERP implementations, Finance transformation, SAP S/4HANA programs, cloud modernization, or enterprise system upgrades. Knowledge of Finance data warehousing, data integration, semantic layers, business intelligence, reporting modernization, or analytics platforms. Experience defining Finance data quality rules, reconciliation needs, validation logic, reporting requirements, and business acceptance criteria. Familiarity with SOX-aware requirements, audit controls, change control, release governance, and data integrity practices. Experience with Enterprise Performance Management tools, including Oracle Essbase or similar budgeting, planning, forecasting, and management reporting platforms. Experience in healthcare, oncology, provider networks, life sciences, or other regulated environments. Strong facilitation, communication, stakeholder management, and executive-facing presentation skills. Travel, Work Environment and Physical Requirements Primary location: Houston, TX; secondary location: Dallas, TX. This is a standard professional office/computer-based role requiring frequent use of business systems, collaboration tools, and virtual or in-person stakeholder meetings. We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here. Our Base Pay Range for this position $111,100 - $185,100 McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKesson's (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages. In light of these scams, please bear the following in mind: McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application. McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail. Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates. McKesson job postings are posted on our career site: . McKesson is an Equal Opportunity Employer McKesson provides equal employment opportunities to applicants and employees, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. For additional information on McKesson's full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page. McKesson is committed to being an Equal Employment Opportunity Employer and offers opportunities to all job seekers including job seekers with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, please contact us by sending an email to (United States) or (Canada) . Resumes or CVs submitted to this email box will not be accepted. Join us at McKesson!

Job Description Location: Santa Monica, New York or Nashville, TN About HYBE Americas HYBE is an entertainment company, global lifestyle platform, and holding company for multiple music labels. It is home to the global girl group KATSEYE and Santos Bravos - the first Latin Pop boy group built using the K-pop methodology - among others, with several new artists in development including projects with Ryan Tedder and under HYBE x Geffen. HYBE builds local subsidiaries to "localize" its K-pop training and production system and develop talent for global releases. HYBE Americas is based in Los Angeles and Mexico City, with additional offices in New York, Miami, Atlanta, and Nashville. Role Overview This is a player-coach role, leading a segment of the Business Intelligence team that supports HYBE's Global Label Services function. You will manage two Data Analysts and own relationship management with key business stakeholders, acting as a thought leader and problem-solving partner, developing and maintaining recurring reporting, and conducting deep analysis labels and business teams rely on for strategy and key decisions. Expect your time to be split between leading and managing your team, and your own hands-on work with our data infrastructure as a senior partner to our label teams. You'll work inside a modern data stack we are actively building, helping shape our semantic layer and BI tools, and partnering closely with data engineering on what gets modeled and how metrics are defined. Fluency in fan culture and how global, modern music companies operate is essential. You should be deeply curious about artists, release and promotion mechanics, and how fandoms drive consumption. You must be able to anticipate which questions matter before a label team asks them. What You'll Do Lead the team Manage, coach, and develop two Data Analysts: set goals, run 1:1s, review their SQL, Python, and dashboards, and give clear, regular feedback. Own the quality bar. Review work before it reaches stakeholders and build QA habits (reconciliation checks, source notes, metric definitions) into the team's routine. Work with our Project Manager to assign work across the two analysts, balancing coverage of the label roster, building depth, and avoiding single points of failure wherever possible. Participate in hiring and onboarding as the team grows. Run Label Services reporting With Project Manager, own intake and prioritization for Global Label Services requests: translate label questions into scoped work, set timelines, and manage stakeholders. Define and maintain the standard set of release and campaign views (streaming, social, and marketing metrics) drawn from internal data and third-party data sources like Luminate, Chartmetric, DSP "for artists" dashboards, social tools (e.g., Supermetrics, Meltwater), and our OpenPlay data. Partner with data engineering to support development of semantic layer, work together to resolve data quality issues at the source rather than in spreadsheets. Hands-on work Own your own projects end-to-end, leveraging your experience and expertise to set the bar for high-quality projects and reporting for the team. Work with analysts to use Python to automate recurring pulls and routine reporting workflows. Take the harder analytical questions yourself, like key campaign and release post-mortems, cross-artist benchmarks, fandom and market comparisons, and turn them into clear business recommendations with context. Partner with label teams Serve as the day-to-day BI point of contact for the Global Label Services team. Present findings to non-technical stakeholders, including senior label leadership, in plain language. Document what the team builds so outputs are discoverable, trusted, and reusable. Required Qualifications Bachelor's degree; 3-5+ years of experience in analytics or business intelligence, ideally in music, entertainment, or media. Experience managing or formally mentoring analysts or interns, including reviewing their technical work. Advanced SQL : complex joins, window functions, and performance-aware queries in a cloud data warehouse (Snowflake, BigQuery, Databricks). Working proficiency in Python for data cleaning and automation. Strong experience building and maintaining dashboards in at least one BI tool (Tableau, Looker, Sigma, or Omni); familiarity with semantic layers or governed metric definitions. Hands-on experience with music data: DSP reporting, Luminate, Chartmetric, or comparable sources, and an understanding of their quirks and limits. Experience at a record label, distributor, or label services company supporting release and marketing teams. Proven ability to prioritize competing requests, and manage stakeholder expectations with grace and tact. Clear written and verbal communication; able to explain data to non-technical and senior audiences. Comfort with ambiguity and a build-in-progress environment. Preferred Qualifications (Pluses, Not Required) Knowledge of the K-pop genre is a plus: major artists, fan culture, and how releases and promotion work in Korea and globally. Korean or Spanish language ability (reading and/or conversational) is a strong plus. Helpful for working with Korean label teams and source material. Familiarity with social analytics platforms and marketing attribution. Experience working across U.S. and other cross-border teams and time zones. Compensation & Benefits Competitive salary based on experience and qualifications. Comprehensive health, dental, and vision insurance. 401(k) with company match. Generous PTO and holiday schedule. Base Salary $110,000 - $140,000 based on location and experience.

Job Description Federal Project - Applicant must be a United States Citizen with the ability to obtain a Public Trust Baer is looking for Oracle Analytic Cloud Developer for a 9-month Federal remote Project Title: Oracle Analytic Cloud Developer Location: Remote (Must be based in US) Duration: 9 months Rate: All-inclusive Alignment: W2 or C2C Overview: The Oracle Analytics Cloud (OAC) Developer is responsible for developing, enhancing, and maintaining reports, dashboards, and data visualizations to support business decision-making. This role focuses on production support, issue resolution, data accuracy, and performance optimization within OAC environments. The ideal candidate has strong expertise in OAC, SQL, data modeling, and data integration, with experience troubleshooting analytics solutions and collaborating with business and technical teams. Description: Develop, enhance, and maintain OAC reports, dashboards, analyses, and data visualizations based on business requirements. Troubleshoot and resolve client-reported issues related to report logic, data discrepancies, access permissions, and performance. Support OAC data models and semantic layers, including subject areas, joins, hierarchies, and calculations. Write and optimize SQL queries to validate data, investigate issues, and improve reporting performance. Perform root-cause analysis and coordinate with data engineering, infrastructure, and business teams to resolve production issues. Implement analytics enhancements and validate reports following data model changes, ETL updates, or platform upgrades. Support data integration processes and troubleshoot data pipeline issues using Oracle Data Integration Cloud Services or similar tools. Maintain technical documentation, troubleshooting procedures, and support records. Assist with OAC administration, including user and role management, environment monitoring, and configuration checks, as needed. Collaborate with cross-functional teams to ensure reliable, accurate, and high-performing analytics solutions. Requirements: 7+ years of advanced experience in Oracle Cloud Infrastructure (OCI), Oracle Analytics Cloud (OAC), Oracle Data Integration Cloud Services, Data Engineering, and SQL. Hands-on experience developing reports and dashboards using Oracle Analytics Cloud (OAC) or Oracle Analytics Server (OAS). Advanced proficiency in OCI, OAC, Oracle Data Integration Cloud Services, Data Engineering, and SQL (P3). Strong knowledge of data modeling, semantic layers, relational databases, and data warehousing. Experience in SQL development, data validation, performance tuning, troubleshooting, and root-cause analysis. Familiarity with ETL/ELT tools such as ODI, Informatica, or Talend. Experience supporting production analytics environments and resolving data and reporting issues. Knowledge of OAC administration and cloud-based data pipelines is preferred. Strong analytical, problem-solving, communication, and documentation skills. Bachelor's Degree Public Trust Security Clearance is the lowest level of additional background screening that the federal government requires for applicants of certain jobs, which includes completing a Standard Form 85 (SF85) form. Company Overview: Baer provides best-in-class engagement experiences for our consultants. Our job requirements are carefully vetted and are typically associated with pivotal programs offering tremendous opportunities to expand your skills leveraging the latest solutions. Baer is an equal opportunity employer including disability/veteran. ALL OPEN JOBS

Job Description Location: Santa Monica, New York or Nashville, TN About HYBE Americas HYBE is an entertainment company, global lifestyle platform, and holding company for multiple music labels. It is home to the global girl group KATSEYE and Santos Bravos - the first Latin Pop boy group built using the K-pop methodology - among others, with several new artists in development including projects with Ryan Tedder and under HYBE x Geffen. HYBE builds local subsidiaries to "localize" its K-pop training and production system and develop talent for global releases. HYBE Americas is based in Los Angeles and Mexico City, with additional offices in New York, Miami, Atlanta, and Nashville. Role Overview This is a player-coach role, leading a segment of the Business Intelligence team that supports HYBE's Global Label Services function. You will manage two Data Analysts and own relationship management with key business stakeholders, acting as a thought leader and problem-solving partner, developing and maintaining recurring reporting, and conducting deep analysis labels and business teams rely on for strategy and key decisions. Expect your time to be split between leading and managing your team, and your own hands-on work with our data infrastructure as a senior partner to our label teams. You'll work inside a modern data stack we are actively building, helping shape our semantic layer and BI tools, and partnering closely with data engineering on what gets modeled and how metrics are defined. Fluency in fan culture and how global, modern music companies operate is essential. You should be deeply curious about artists, release and promotion mechanics, and how fandoms drive consumption. You must be able to anticipate which questions matter before a label team asks them. What You'll Do Lead the team Manage, coach, and develop two Data Analysts: set goals, run 1:1s, review their SQL, Python, and dashboards, and give clear, regular feedback. Own the quality bar. Review work before it reaches stakeholders and build QA habits (reconciliation checks, source notes, metric definitions) into the team's routine. Work with our Project Manager to assign work across the two analysts, balancing coverage of the label roster, building depth, and avoiding single points of failure wherever possible. Participate in hiring and onboarding as the team grows. Run Label Services reporting With Project Manager, own intake and prioritization for Global Label Services requests: translate label questions into scoped work, set timelines, and manage stakeholders. Define and maintain the standard set of release and campaign views (streaming, social, and marketing metrics) drawn from internal data and third-party data sources like Luminate, Chartmetric, DSP "for artists" dashboards, social tools (e.g., Supermetrics, Meltwater), and our OpenPlay data. Partner with data engineering to support development of semantic layer, work together to resolve data quality issues at the source rather than in spreadsheets. Hands-on work Own your own projects end-to-end, leveraging your experience and expertise to set the bar for high-quality projects and reporting for the team. Work with analysts to use Python to automate recurring pulls and routine reporting workflows. Take the harder analytical questions yourself, like key campaign and release post-mortems, cross-artist benchmarks, fandom and market comparisons, and turn them into clear business recommendations with context. Partner with label teams Serve as the day-to-day BI point of contact for the Global Label Services team. Present findings to non-technical stakeholders, including senior label leadership, in plain language. Document what the team builds so outputs are discoverable, trusted, and reusable. Required Qualifications Bachelor's degree; 3-5+ years of experience in analytics or business intelligence, ideally in music, entertainment, or media. Experience managing or formally mentoring analysts or interns, including reviewing their technical work. Advanced SQL : complex joins, window functions, and performance-aware queries in a cloud data warehouse (Snowflake, BigQuery, Databricks). Working proficiency in Python for data cleaning and automation. Strong experience building and maintaining dashboards in at least one BI tool (Tableau, Looker, Sigma, or Omni); familiarity with semantic layers or governed metric definitions. Hands-on experience with music data: DSP reporting, Luminate, Chartmetric, or comparable sources, and an understanding of their quirks and limits. Experience at a record label, distributor, or label services company supporting release and marketing teams. Proven ability to prioritize competing requests, and manage stakeholder expectations with grace and tact. Clear written and verbal communication; able to explain data to non-technical and senior audiences. Comfort with ambiguity and a build-in-progress environment. Preferred Qualifications (Pluses, Not Required) Knowledge of the K-pop genre is a plus: major artists, fan culture, and how releases and promotion work in Korea and globally. Korean or Spanish language ability (reading and/or conversational) is a strong plus. Helpful for working with Korean label teams and source material. Familiarity with social analytics platforms and marketing attribution. Experience working across U.S. and other cross-border teams and time zones. Compensation & Benefits Competitive salary based on experience and qualifications. Comprehensive health, dental, and vision insurance. 401(k) with company match. Generous PTO and holiday schedule. Base Salary $110,000 - $140,000 based on location and experience.

Job Description This role is primarily focused on data engineering, transformation frameworks, orchestration, and system integrations. While the team builds applications on top of their platform, dedicated application engineering resources lead full-stack UI development. This position will focus on building and maintaining reliable data pipelines, implementing business logic, and supporting scalable data solutions that power those applications. The ideal candidate has strong hands-on experience with modern cloud data platforms (Snowflake and/or Databricks), transformation tooling (dbt), and orchestration frameworks (Airflow or similar). This individual works effectively in a business-aligned environment, partnering with investment and operations teams to deliver secure and scalable data solutions. Primary Responsibilities Credit Data Warehouse Architecture & Development (40%) Build and enhance scalable data models within Snowflake (and/or Databricks where applicable) across landing, integration, and presentation layers, following established architectural patterns. Develop and maintain transformation logic using dbt, ensuring modular, testable, and well-documented models Optimize SQL performance and warehouse resource usage for large-scale financial datasets Implement data quality checks, validation rules, and audit controls Contribute to metadata-driven approaches that support flexible integrations and reporting needs. Support lineage, governance, and maintainability of CDW assets through documentation and adherence to engineering standards. Design data models optimized for reporting and BI consumption, partnering closely with the Credit IQ (Power BI) team to ensure scalable semantic layers and performant analytics Workflow Orchestration & Pipeline Engineering (25%) Build and support data pipelines orchestrated through Airflow Develop and maintain DAGs/workflows for ingestion, transformation, external extracts, and API integrations. Support improvements to pipeline reliability, monitoring, and error handling in production environments. Collaborate with DevOps to ensure CI/CD alignment and production stability Support modernization of legacy orchestration processes into Airflow-based frameworks Integrations & Data Products (20%) Build and support integrations with external vendors, fund administrators, trustees, and internal systems. Build scalable export frameworks (SFTP, API, file-based extracts) driven by configuration and metadata Support data consumption by internal applications and analytics tools Collaborate with application engineering teams to provide well-structured datasets and data interfaces for application use. Applied AI & Intelligent Data Use Cases (10%) Support AI-enabled workflows by preparing structured and unstructured data for retrieval and analysis use cases Assist in enabling retrieval-based workflows leveraging CDW datasets where applicable Ensure AI-related datasets follow security and governance standards Cross-Functional Collaboration & Technical Leadership (5%) Participate in code reviews and provide guidance to junior and offshore contributors Coordinate assigned work with offshore resources to ensure clarity of requirements and timely delivery Work with investment and operations teams to translate business workflows into scalable data solutions Promote clear documentation and adherence to engineering best practices Requirements Education & Certificates Bachelor's degree, required Concentration in computer science, engineering, or a related quantitative field, preferred Master's degree preferred Professional Experience Minimum of 6 years of overall relevant technical experience, required Experience in data engineering, platform engineering, or backend-focused software engineering roles, required Strong hands-on experience designing and operating solutions in Snowflake and/or Databricks (or comparable modern cloud data warehouse/lakehouse platforms) Experience building and deploying data platforms in Azure and/or AWS cloud environments Strong experience writing and optimizing SQL for analytical and financial datasets Hands-on experience with dbt for transformation management, testing, and modular model development Experience developing and supporting Airflow-based orchestration pipelines (or equivalent), including workflow design and monitoring Experience building and maintaining enterprise-grade data pipelines across ingestion, transformation, and presentation layers Experience integrating enterprise systems via APIs, file-based transfers (SFTP), or event-driven workflows Exposure to financial services, alternative asset management, or credit products strongly preferred Experience collaborating with offshore or distributed engineering teams preferred Experience supporting reporting and BI environments (e.g., Power BI), including building reporting-friendly data models and optimizing warehouse performance for analytics workloads Python experience for pipeline tooling, automation, and integration services Experience with Azure services (e.g., Azure Data Factory, Azure Storage, Azure AD) and/or AWS services (e.g., S3, IAM, Lambda, ECS) Experience building or supporting data services consumed by applications Exposure to applied AI or LLM-enabled workflows in a production setting Familiarity with Power BI or comparable BI/reporting tools and semantic modeling concepts Strong SQL and analytical data modeling skills Snowflake and/or Databricks fundamentals, including performance and cost considerations dbt framework design and transformation best practices Airflow (or equivalent) orchestration and production support experience Azure and/or AWS cloud-native data architecture API integration and service-oriented data patterns Data quality, lineage, governance, and audit controls Competencies & Attributes Strong problem-solving and analytical skills Ability to translate business workflows into scalable data solutions Clear communication with both technical and non-technical stakeholders Understanding of BI/reporting architecture, semantic modeling, and analytics performance

Job Description We are actively interviewing for the following job. If interested please apply now. About the Opportunity We are at a pivotal point in our growth across the Mid-Atlantic region and are one year into a three-year enterprise replatforming initiative. Operating on a cloud-first, "buy over build" strategy within a Microsoft Azure environment, we are modernizing our core ERP and operating platforms while rolling out enterprise-grade data and analytics capabilities. Reporting directly to the CTO, the IT Technical Lead will serve as the Lead Architect for the business. You will own the full-scale technical picture-specifically driving application integrations, data pipelines, and Databricks architecture-while mentoring our internal engineering and operational teams. We are looking for a modern, collaborative leader who thrives as a translator between business stakeholders and technical execution, and who is passionate about developing people and building scalable enterprise architectures. Please note: This role requires working on-site in Annapolis, MD. If you are open to a high-impact architecture and leadership opportunity in the Annapolis area, we would love to speak with you. What You Will Do Data Architecture, Integrations & Cloud Engineering Databricks & Data Pipelines: Own the architecture, integration, and CI/CD pipelines for our data environment, ensuring seamless data flow from core enterprise applications into Databricks and Microsoft Power BI . Semantic Modeling: Build, analyze, and troubleshoot semantic models to support enterprise reporting and bleeding-edge analytics. Application Integrations: Lead the design and implementation of API and appliance-based integrations across our Microsoft Azure cloud environment, connecting our new ERP, operational platforms, and legacy private-cloud systems. Enterprise Reference Architecture: Translate corporate business goals into scalable technical roadmaps, standardizing architectures and development guidelines across all regional operating divisions. Emerging Tech Evaluation: Evaluate emerging technologies (such as AI logistics engines and edge analytics) and recommend strategic upgrades that drive operational efficiency. Architecture Governance & Delivery CI/CD & Code Standards: Enforce strict CI/CD pipeline standards, code reviews, and technical documentation practices. Change Management: Chair the corporate Change Advisory Board (CAB) and coordinate software upgrade cycles, integrations, and cutovers to ensure zero operational disruption. Partner & Vendor Alignment: Act as the primary technical interface for third-party systems integrators, implementation partners, and software/hardware vendors, managing technical deliverables and risk registers for multi-million-dollar transformation initiatives. Team Leadership & Mentorship Mentor & Grow Talent: Lead, mentor, and direct cross-functional technical staff (integration, network, security, and operational support teams). People-First Culture: Establish skills matrices, performance objectives, and clear career growth frameworks. Foster a supportive environment where team members are encouraged to learn, innovate, and develop both their technical and soft skills. Business Translation: Bridge the gap between technical teams and non-technical executives, translating business requirements into clear architectural plans. What We Are Looking For Core Data & Integration Tech (Must-Have): Proven hands-on experience in Databricks architecture, application/API integrations, and CI/CD pipelines within a Microsoft Azure and Power BI ecosystem. (Note: Strong Databricks experience is highly preferred; however, exceptional candidates who check every other box and possess deep Snowflake architecture experience will also be considered.) Experience: 8+ years of progressive engineering experience across IT/OT and cloud environments, with at least 2-3+ years in a Technical Lead, Solution Architect, or Engineering Management role. Industry Background: 3+ years of experience in construction, materials handling, logistics, transport, manufacturing, or a related heavy industrial/multi-site environment. Leadership & Communication: Exceptional communication and executive presentation skills. We need a collaborative leader who excels at translating between business and technology and who prioritizes mentoring and elevating their team. Education & Certifications: Bachelor's or Master's degree in Computer Science, Systems Engineering, Software Engineering, or a related technical field preferred. Certifications such as Azure Solutions Architect, Databricks certifications, TOGAF, or ITIL v4 are a strong plus.

Job Description Rate: $60-65/hr C2C Position Overview: The Senior AI/ML Data Platform Engineer will lead the architecture, development, and continuous improvement of shared enterprise data products and AI-enabled data services. The role focuses on scalable data platforms, real-time streaming, data quality, governance, API design, and integration of AI/ML capabilities into data workflows. Key Requirements: 10+ years of experience in data engineering, ML engineering, or data platform development, including 2+ years designing or operating production data products or data services. Bachelor's degree in Computer Science, Data Science, Engineering, or a related field; master's degree preferred. Expert-level SQL and strong Python programming skills. Experience with AWS, Azure, or GCP data platforms, including Amazon Redshift, AWS Glue, Azure Synapse, Azure Data Factory, BigQuery, Dataflow, Databricks, or Snowflake. Production experience with Apache Kafka, Amazon Kinesis, Apache Flink, or Spark Structured Streaming. Strong understanding of data modeling and architecture patterns, including data vault, lakehouse, and data mesh. Experience with data quality frameworks, data catalogs, data lineage, API design, data contracts, and event-driven architectures. Experience integrating ML models into data pipelines or developing AI-powered data services. Experience with data access controls, attribute-level masking, audit logging, and governance. Strong architectural leadership, technical documentation, mentoring, and cross-team collaboration skills. Preferred Experience: Data mesh, federated data architecture, and enterprise data product initiatives. LLM applications for text-to-SQL, document extraction, semantic search, and automated enrichment. Government, public sector, or highly regulated environments. Data privacy and security requirements, including PII protection, CJIS, HIPAA, and IRS Publication 1075, where applicable. NIST AI Risk Management Framework and responsible AI practices. Data platform FinOps, cloud cost attribution, storage tiering, and query optimization.

Job Description Project Description: We are looking for a hands-on BI Platform Operations Engineer to provide production operational support, administration, maintenance, and technical troubleshooting for our enterprise Business Intelligence platforms and associated AWS services. The role will primarily support Tableau and Amazon QuickSight / Amazon Quick Suite, including a custom BI-as-a-Service (BIaaS) platform built on top of Amazon QuickSight. The BIaaS platform consists of multiple backend services, RESTful APIs, AWS serverless and data services, and a web-based user interface. This is primarily a platform engineering and production support role, rather than a dashboard/report development position. The successful candidate will be comfortable troubleshooting across BI, application, API, data, AI-assisted analytics, and cloud infrastructure layers and working with engineering teams to maintain a reliable and stable production service. For Canada this role is for subcontractor. For NYC: compensation 00 UAS Gross per year and based on your interview results. Responsibilities: Production Operations & Support Provide day-to-day production operational support for Tableau, Amazon QuickSight / Quick Suite, the BI-as-a-Service platform, and its supporting AWS services. Monitor platform availability, performance, capacity, scheduled workloads, and overall service health. Investigate and resolve production incidents, user issues, failed jobs, connectivity problems, access issues, API failures, and platform errors. Perform root-cause analysis and work with engineering, application, data, and infrastructure teams to resolve recurring issues. Support incident, problem, release, and change-management processes. Develop and maintain operational runbooks, troubleshooting procedures, and support documentation. Identify opportunities to automate repetitive operational and administrative activities. Proactively identify platform health, reliability, and supportability improvements. Tableau Platform Administration Administer and maintain the enterprise Tableau Server environment. Support Tableau Server infrastructure, configuration, upgrades, patching, and platform maintenance. Manage sites, projects, users, groups, permissions, and content access. Troubleshoot extracts, refresh schedules, data-source connectivity, authentication, and performance issues. Monitor Tableau Server processes, logs, resource utilization, and platform health. Assist with platform upgrades, migrations, configuration changes, and infrastructure-related activities. Amazon QuickSight / Quick Suite Administration, Authoring & Support Provide day-to-day Amazon QuickSight / Quick Suite production support, administration, and operational troubleshooting. Support the lifecycle, administration, and troubleshooting of BI and analytics assets, including: Analyses Dashboards Datasets Data Sources Themes Folders Templates Topics and conversational BI capabilities Other QuickSight / Quick Suite assets and platform objects Troubleshoot issues related to creating, updating, publishing, sharing, and accessing analyses and dashboards. Support QuickSight authoring capabilities and assist authors with analysis, visualization, dataset, data-source, dashboard, and semantic configuration issues. Troubleshoot dataset ingestion and refresh failures, including SPICE ingestion, scheduled refreshes, and direct-query scenarios. Diagnose data-source connectivity and access issues involving Amazon Athena and other supported data sources. Support and troubleshoot themes and reusable assets, including permissions and sharing. Manage and troubleshoot users, groups, namespaces, folders, asset permissions, and access controls. troubleshoot dashboard and analysis permissions, sharing, ownership, and access issues. Understand and troubleshoot security and AWS integrations, including IAM-based access and permissions. Support and troubleshoot programmatic management of QuickSight assets using QuickSight APIs and AWS SDKs. Troubleshoot API operations involving analyses, dashboards, datasets, data sources, themes, permissions, and other supported assets. Support embedded QuickSight capabilities and troubleshoot embedding, authentication, authorization, and access-related issues where applicable. Amazon Q / Generative BI & Quick Suite Capabilities Support and develop operational familiarity with Amazon Q capabilities within QuickSight / Quick Suite, including natural-language and generative BI experiences. Support Amazon Q Topics and associated semantic configurations used to provide business context for natural-language analytics. Troubleshoot user access, permissions, data availability, semantic configuration, and other issues affecting Amazon Q experiences. Support conversational BI capabilities that allow users to ask questions of enterprise data using natural language. Support newer Quick Suite conversational and agentic experiences, including chat agents, agents, and spaces, where adopted by the platform. Understand how Spaces organize relevant data, content, context, and resources used by Quick Suite experiences. Assist with operational support and troubleshooting of Amazon Q / Quick Suite agents, including access, configuration, underlying data/content availability, and integration-related issues. Work with platform and engineering teams as Amazon Q and Quick Suite capabilities evolve and are incorporated into the BI-as-a-Service offering. BI-as-a-Service Platform Provide operational and technical support for our internally developed BI-as-a-Service platform built on Amazon QuickSight, including the AWS data, API, serverless, monitoring, and analytics services that underpin the platform. Platform & QuickSight Integration Understand the end-to-end BIaaS architecture and troubleshoot issues across APIs, backend services, AWS infrastructure, data services, QuickSight, and Quick Suite capabilities. Support integrations with Amazon QuickSight using QuickSight APIs and AWS SDKs. Troubleshoot the programmatic creation, update, deployment, sharing, and management of QuickSight assets. Troubleshoot asset provisioning, permissions, embedding, authentication, authorization, and other QuickSight integration workflows. Analyze application and AWS service logs to diagnose production issues. Work closely with platform engineering and development teams to identify defects and implement sustainable fixes. Assist with deployments, configuration changes, environment maintenance, and production releases. AWS Data & Analytics Services Support and troubleshoot Amazon Athena queries and integrations used by BI applications and reporting workloads. Understand Athena connectivity, permissions, workgroups, query execution, and common performance or operational issues. Support the AWS Glue Data Catalog, including databases, tables, metadata, schemas, partitions, and integrations with Athena and QuickSight. Troubleshoot metadata, schema, partition, and data-discovery issues involving the Glue Data Catalog. Understand and support AWS Lake Formation permissions and data-access controls. Troubleshoot access issues across Lake Formation, Glue Data Catalog, Athena, IAM, and QuickSight. Understand the end-to-end data-access path from underlying data sources through Athena and the Glue Data Catalog to QuickSight. AWS Serverless & REST API Services Support and troubleshoot AWS Lambda functions used by the BI-as-a-Service platform. Understand Lambda configuration, IAM roles, environment variables, triggers, execution failures, and timeouts. Support Amazon API Gateway endpoints integrated with Lambda and other backend services. Troubleshoot API Gateway routing, authentication/authorization, request and response handling, integration failures, and HTTP errors. Understand and troubleshoot RESTful APIs, including HTTP methods, headers, request/response payloads, authentication, authorization, and error handling. Use API testing and troubleshooting techniques to diagnose service integration issues. Understand interactions between API Gateway, Lambda functions, backend services, AWS APIs, and QuickSight APIs. Monitoring & Observability Use Amazon CloudWatch to monitor and troubleshoot the BIaaS platform and its supporting AWS services. Analyze CloudWatch Logs, metrics, dashboards, and alarms to identify and diagnose production issues. Troubleshoot Lambda executions and API Gateway requests using CloudWatch logging and metrics. Correlate events and logs across multiple services to identify the source of end-to-end transaction failures. Support and improve operational monitoring, alerting, and platform-health dashboards. Identify monitoring gaps and opportunities to improve proactive detection of production issues. Mandatory Skills Description: Required Skills & Experience Strong hands-on experience supporting enterprise BI platforms in production environments. Strong experience with Tableau Server administration and operational support. Strong hands-on experience with Amazon QuickSight administration, authoring . click apply for full job details

Job Description Job Description Role Overview We are hiring Forward Deployed AI Engineers (FDEs) to partner with one of the largest healthcare payers in the U.S. to drive AI-led transformation across core business workflows . This is not a traditional engineering role. You will work directly with business and technology teams to design, build, and deploy AI agents that transform how healthcare operations function, while enabling teams to become AI-native and self-sufficient . You will operate at the intersection of AI, engineering, and healthcare operations , delivering real-world impact across critical payer workflows. Key Responsibilities1. AI-Driven Business Transformation Redesign healthcare processes using AI-first principles Identify opportunities to replace or augment manual workflows with AI agents Translate business problems into working AI solutions 2. Agentic AI Design & Deployment Design, build, and deploy AI agents for enterprise workflows Implement multi-agent systems using LLMs (prompting, memory, tool usage) Rapidly prototype and productionize solutions using platforms such as: OpenAI Anthropic Google (Gemini) 3. Forward Deployed Execution Work directly with client teams (business + IT) to: Whiteboard solutions Build prototypes in days/weeks Deploy and iterate rapidly Operate as a trusted advisor and builder 4. AI-Augmented SDLC Leverage AI across the software lifecycle: Code generation and refactoring Automated testing and validation Documentation and observability Drive productivity improvements across engineering teams 5. Enablement & Adoption Train business and operations teams to: Use AI tools and agents effectively Build and iterate workflows independently Develop reusable playbooks and frameworks Domain Focus (Healthcare Payer Workflows) Claims Processing & Adjudication Prior Authorization Member & Provider Contact Center Provider Data Management Care Management & Utilization Review Revenue Cycle & Payment Integrity Required SkillsTechnical Strong software engineering background ( Python, APIs, microservices ) Experience with LLMs, prompt engineering, and AI frameworks Familiarity with agent frameworks (LangChain, Semantic Kernel, etc.) AI & Data Experience building AI/ML or LLM-powered applications Understanding of structured and unstructured data pipelines Knowledge of model evaluation, monitoring, and governance Cloud Experience with: AWS Azure Consulting Mindset Strong communication and stakeholder management Ability to work directly with business teams Experience in rapid prototyping and iterative delivery Preferred Experience in U.S. healthcare payer or PBM environments Understanding of claims, prior auth, or care management workflows Familiarity with regulatory/compliance (HIPAA) Experience 6-12+ years in software engineering, AI, or related roles Prior client-facing / consulting experience preferred What Makes This Role Unique Work at the forefront of AI-driven enterprise transformation Build real-world AI agents replacing traditional workflows Direct business impact through a forward-deployed model Opportunity to scale from pilot solutions to enterprise-wide programs Success Metrics Number of workflows transformed using AI Reduction in manual effort and cost-to-serve Adoption of AI tools by business teams Speed from prototype to production

This job is with Gilead Sciences Inc., an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. At Gilead, we're creating a healthier world for all people. For more than 35 years, we've tackled diseases such as HIV, viral hepatitis, COVID-19 and cancer - working relentlessly to develop therapies that help improve lives and to ensure access to these therapies across the globe. We continue to fight against the world's biggest health challenges, and our mission requires collaboration, determination and a relentless drive to make a difference. Every member of Gilead's team plays a critical role in the discovery and development of life-changing scientific innovations. Our employees are our greatest asset as we work to achieve our bold ambitions, and we're looking for the next wave of passionate and ambitious people ready to make a direct impact. We believe every employee deserves a great leader. People Leaders are the cornerstone to the employee experience at Gilead and Kite. As a people leader now or in the future, you are the key driver in evolving our culture and creating an environment where every employee feels included, developed and empowered to fulfil their aspirations. Join Gilead and help create possible, together. Job Description As part of Gilead's enterprise AI and digital strategy to accelerate insights and decision making, we are seeking an Associate Director, Data/AI Solution Architect to lead the design of Data and AI solutions across the Commercial (Marketing & Sales) digital content lifecycle. In this role, you will partner closely with business stakeholders, and Data/AI Product Owners, Technical Delivery Leads and Platform Leads to determine the right solution architecture for predictive analytics and AI driven insights. You will drive technical excellence through architectural design, modeling approach, and platform selection-ensuring scalable solutions, aligned to Gilead standards, that translate complex digital needs into actionable insights. This position will report to the Director, Data/AI, Commercial Digital and is based in Raleigh, NC (hybrid eligible). As a Associate Director, Data/AI Solution Architect, US Commercial Digital Marketing , at Gilead you will Key Responsibilities Determine end to end Data/AI solution architecture for digital marketing use cases, including predictive modeling and advanced analytics across the digital content lifecycle Design how solutions are delivered, including data flows, modeling approaches, integration patterns, and analytics outputs on AWS & Databricks platforms Apply enterprise and domain architecture and tool standards, while providing input to inform and evolve those standards Evaluate build vs. buy options and recommend platforms, tools, and frameworks aligned with enterprise strategy Develop solution blueprints and lifecycle maps to guide implementation from data creation through insight generation Define data quality, observability, and validation expectations for Commercial Digital data products, ensuring data is complete, accurate, timely, trusted, and fit for analytics, AI, and downstream business decision-making. Ensure data products and solution designs include clear business context, ownership, lineage, metadata, cataloging, sensitivity classification, refresh frequency, usage guidance, and traceability from source data through transformation, model input/output, insight generation, and business action. Develop and maintain data architecture artifacts, including source-to-target flows, integration patterns, canonical data models, semantic layers, master/reference data dependencies, business rules, key entities, metrics, and downstream consumption patterns. Partner with Enterprise Architecture and platform teams to maintain application, capability, integration, lifecycle, and data-flow mappings in Enterprise system of record, supporting architecture reviews, impact assessments, technology rationalization, and alignment with enterprise standards. Partner with Capability Leads and Product Owners to translate business capability needs into well-structured solution designs, data architecture, platform dependencies, and technical delivery guardrails. Support the AI, data science, and data engineering teams by defining the data architecture, feature inputs, model integration patterns, traceability, and operational data requirements needed to move AI use cases from concept to production Ensure AI solution designs include the required data readiness, context, lineage, integration, governance, monitoring, and handoff requirements so models and insights can be deployed, maintained, and reused across Commercial Digital capabilities. Ensure solution designs support scalability, reusability, performance, security, and governance Maintain clear technical documentation, design artifacts, and architectural diagrams to support delivery and long term maintainability Basic Qualifications Bachelor's Degree and Ten Years' Experience OR Masters' Degree and Eight Years' Experience OR PhD and Two Years' Experience Preferred Qualifications Significant experience designing data, analytics, and AI solutions, with demonstrated depth in architecture and advanced analytics Proven experience with predictive modeling, machine learning, and analytics solution design; hands on experience on AWS & Databricks platforms strongly preferred Deep understanding of emerging data and AI architectures, platforms, tools and analytics stacks Previous experience designing solutions across Life Sciences Commercial Marketing & Sales digital platforms, content, or engagement data required Ability to translate complex business needs into technical designs and influence stakeholders without direct authority Strong communication, collaboration, and stakeholder management skills, with the ability to engage effectively with both technical and non technical partners People Leader Accountabilities : •Create Inclusion - knowing the business value of diverse teams, modeling inclusion, and embedding the value of diversity in the way they manage their teams. •Develop Talent - understand the skills, experience, aspirations and potential of their employees and coach them on current performance and future potential. They ensure employees are receiving the feedback and insight needed to grow, develop and realize their purpose. •Empower Teams - connect the team to the organization by aligning goals, purpose, and organizational objectives, and holding them to account. They provide the support needed to remove barriers and connect their team to the broader ecosystem. The salary range for this position is: $168,980.00 - $218,680.00. Gilead considers a variety of factors when determining base compensation, including experience, qualifications, and geographic location. These considerations mean actual compensation will vary. This position may also be eligible for a discretionary annual bonus, discretionary stock-based long-term incentives (eligibility may vary based on role), paid time off, and a benefits package. Benefits include company-sponsored medical, dental, vision, and life insurance plans . For additional benefits information, visit: Eligible employees may participate in benefit plans, subject to the terms and conditions of the applicable plans. For jobs in the United States: Gilead Sciences Inc. is committed to providing equal employment opportunities to all employees and applicants for employment, and is dedicated to fostering an inclusive work environment comprised of diverse perspectives, backgrounds, and experiences. Employment decisions regarding recruitment and selection will be made without discrimination based on race, color, religion, national origin, sex , age, sexual orientation, physical or mental disability, genetic information or characteristic, gender identity and expression, veteran status, or other non-job related characteristics or other prohibited grounds specified in applicable federal, state and local laws. In order to ensure reasonable accommodation for individuals protected by Section 503 of the Rehabilitation Act of 1973, the Vietnam Era Veterans' Readjustment Act of 1974, and Title I of the Americans with Disabilities Act of 1990, applicants who require accommodation in the job application process may contact for assistance. For more information about equal employment opportunity protections, please view the 'Know Your Rights' poster. NOTICE: EMPLOYEE POLYGRAPH PROTECTION ACT YOUR RIGHTS UNDER THE FAMILY AND MEDICAL LEAVE ACT Gilead Sciences will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer . click apply for full job details

Join a team where innovation meets mission. Our AI, cloud, cyber, and modernization solutions save agencies thousands of hours, safeguard national security, and strengthen health and humanitarian missions worldwide. With more than 1,700+ team members, 1,500+ AI & data experts, and 100+ prime contracts, we deliver at scale and with purpose. We've been recognized as a Top Workplace by The Washington Post for six consecutive years and named to the Inc. 5000 list of Fastest-Growing Private Companies in 13 of the past 14 years. Credence is a welcoming environment for those looking to grow and make a meaningful impact. We encourage employees to push boundaries and help solve critical, world-changing federal challenges. Credence has an immediate need for an experienced Senior Google Cloud Platform Looker Developer to support the Defense Automatic Addressing System Digital Business Transformation Reports Modernization team. This hands-on software development role will design, build, integrate, test, deploy, troubleshoot, and sustain enterprise analytics applications using Google Cloud Platform, Looker Enterprise, LookML, and Looker Studio or Looker Studio Pro. The developer will translate functional and technical requirements into production-ready Looker applications, governed semantic models, dashboards, and cloud integrations. The role requires advanced LookML and SQL development, experience with cloud data platforms and APIs, disciplined source-control and deployment practices, and the ability to independently resolve application, data, security, and performance issues. The Senior Developer will also conduct technical reviews, establish reusable development patterns, and mentor other developers. Requirements U.S. citizenship and an active DoD Secret clearance at the time of hire, with the ability to maintain required Government access and suitability. Bachelor's degree in Computer Science, Software Engineering, Information Technology, Information Systems, Data Engineering, or a closely related technical discipline, or an approved equivalent combination of education and experience. At least seven years of experience in business intelligence application development, cloud application development, data engineering, or enterprise reporting development, including at least five years of hands-on development in modern business intelligence platforms. At least three years of hands-on Google Looker Enterprise and LookML development experience, including production semantic models, Explores, dashboards, reusable components, access controls, testing, deployment, and sustainment. Hands-on experience developing Looker Studio or Looker Studio Pro reports, reusable data sources, calculated fields, controls, connectors, and governed sharing configurations. Advanced SQL development and performance-tuning skills using BigQuery and at least one additional enterprise platform such as Amazon Redshift or Oracle. Working knowledge of Google Cloud Platform services used for secure analytics solutions, including BigQuery, Identity and Access Management, Cloud Storage, logging, monitoring, and application integration. Experience integrating reporting applications with data sources, APIs, identity services, and cloud components; experience with Looker APIs, embedded analytics, extensions, JavaScript, or Python is strongly desired. Experience with Git-based version control, code reviews, branching, release management, automated validation, and continuous integration and delivery practices. Strong testing and troubleshooting skills across LookML, SQL, data models, dashboards, permissions, integrations, deployment configurations, and application performance. Experience applying secure coding, role-based access, least-privilege controls, auditing, data-protection, and Section 508 accessibility requirements. Experience leading technical design and code reviews, establishing development standards, mentoring developers, and communicating technical risks and recommendations. Experience working in Scrum, SAFe, or another Agile software delivery environment. Current Security Plus CE or another contract-approved certification meeting DoD 8570 or 8140 IAT Level II requirements. Strong technical writing and communication skills, including the ability to document solution designs, code, configuration, testing, deployment, and operational procedures. Preferred Qualifications Google Cloud Professional Data Engineer, Professional Cloud Developer, Associate Cloud Engineer, or another relevant Google Cloud certification. Experience with data modeling, dimensional modeling, ETL or ELT pipelines, data quality controls, metadata, lineage, and enterprise data governance. Experience modernizing legacy reporting applications and validating data, calculations, security, and performance during platform migrations. Experience supporting DLA, DoD, or another federal agency in a controlled cloud environment; a current Common Access Card is preferred. Work Environment This position supports a collaborative federal delivery team and requires adherence to program security, access, and onsite or hybrid work requirements Salary Range: $150,000 - $190,000 annually. Actual compensation will be determined based on the selected candidate's experience, education, certifications, skills, and overall qualifications. Benefits Health Care Plan (Medical, Dental & Vision) Retirement Plan (401k, IRA) Life Insurance (Basic, Voluntary & AD&D) Paid Time Off (Vacation, Sick & Public Holidays) Family Leave (Maternity, Paternity) Short Term & Long Term Disability Training & Development Free Food & Snacks Wellness Resources Stock Option Plan

Job Description Job Description About NewsBreak Local life runs on local information. What happened down the street? Who can fix this? Where should we go tonight? NewsBreak started in 2015 to answer these questions, and today more than 40 million people a month rely on us to follow what's going on in their zip code. Three platforms with one vision: powering local life. Led by founder and CEO Jeff Zheng, NewsBreak is our local life and news platform; Nearby AI connects people with local businesses; and NDot AI helps publishers and creators grow and earn. Building for the long term. A $115 million Series C made us a unicorn in 2021, and we keep investing in our people. We're Great Place to Work certified and named to Fast Company 's Best Workplaces for Innovators (2025) and Fortune 's Best Workplaces in the Bay Area (2026). Everyone makes an impact. Whether you write code, shape products, tell our story, or run the business, we want people who own projects end to end, stay curious, and speak up. Join us. Learn more at: NewsBreak, Nearby AI, NDot AI About the Role We are looking for a Machine Learning Engineer to build intelligent systems that connect consumers with relevant local information, businesses, and services. You will work across areas such as search, recommendation, ranking, retrieval, user-intent understanding, personalization, and marketplace matching. Depending on your background and interests, you may focus on understanding consumer demand, improving search and recommendation relevance, or building models that more effectively match users with local supply. This is a hands-on role with the opportunity to take machine learning solutions from problem definition and experimentation through production deployment and iteration. We welcome candidates across a range of experience levels, and the scope and level of the role will be calibrated based on the candidate's experience. What You'll Do Build and improve machine learning models for search, recommendation, ranking, retrieval, matching, and personalization. Develop systems that understand user queries, behaviors, preferences, and context. Apply embeddings, natural language processing, large language models, and modern retrieval techniques to connect consumer demand with relevant local content, businesses, or services. Build and optimize end-to-end ML pipelines, from data preparation and model training to online serving and monitoring. Partner with product, engineering, and data teams to define problems, identify opportunities, and translate business needs into scalable ML solutions. Design and analyze online and offline experiments to measure model quality and product impact. Improve key product outcomes such as relevance, engagement, conversion, retention, and marketplace efficiency. Explore new ML and LLM techniques and bring them into production where they can deliver measurable value. What We're Looking For Experience building machine learning, data mining, search, recommendation, ranking, NLP, or related systems through academic projects, internships, or industry work. Strong programming skills in Python, Java, C++, or another relevant language. Solid understanding of machine learning fundamentals, data structures, algorithms, and statistical analysis. Experience with one or more of the following: Search, retrieval, or learning-to-rank Recommendation or personalization Query understanding, intent classification, or NLP Embeddings, semantic search, or large language models Matching, marketplace optimization, or dispatch Ability to work with large-scale or complex datasets and translate ambiguous problems into practical solutions. Strong collaboration and communication skills. Interest in building production systems that serve real users and deliver measurable product impact. Nice to Have Experience deploying and maintaining machine learning models in production. Experience with experimentation, including A/B testing, causal analysis, or marketplace experiments. Familiarity with deep learning frameworks and ML infrastructure, such as PyTorch, TensorFlow, Spark, Kubernetes, or feature and model-serving platforms. Experience building taxonomies, user-interest representations, knowledge graphs, or behavioral models. Experience applying LLMs to search, recommendation, classification, or information retrieval. Background in local search, local services, maps, commerce, marketplaces, delivery, mobility, or location-based products. Experience at a consumer internet, search, recommendation, advertising, e-commerce, or marketplace company. Annual Base Pay Range $190,000 - $300,000 The US base salary range for this full-time position will vary based on job-related skills, level, experience, geographic location, and relevant education or training. At NewsBreak, we design our overall rewards package to attract top talent. Depending on the position and level, the role may also be eligible for a discretionary bonus and equity. Your recruiter can share more details during the hiring process. The US base salary range for this full-time position is listed below. Pay may vary based on a number of factors including job-related skills, level, experience, geographic location and relevant education or training. At NewsBreak, we design our overall rewards package to attract top talents. Depending on the position, the role may also be eligible for discretionary bonus and options. Your recruiter can share more details during the hiring process. Annual Base Pay Range $190,000-$300,000 USD CPRA Privacy Notice for California Candidates

Job Description Job Description: C5MI is not your typical consulting firm. We are a high-performance team of SAP and supply chain experts who solve complex, mission critical challenges for organizations that cannot afford failure. We hire consultants who thrive in complexity, move fast, take ownership, and deliver under pressure. At C5MI, you will not be siloed or stuck in theory. You will be hands on, client facing, and directly influencing outcomes that matter. Our culture rewards initiative, accountability, and continuous growth. This is a place where your expertise is valued, your work is meaningful, and your performance truly matters. If you're energized by learning through real-world challenges, collaborating with top-tier talent, and expanding your capabilities every day, C5MI is where strong consultants level up. Position Summary: The Industry 4.0 Solution Engineer - Production Analytics is a delivery-focused, client-facing technical role responsible for building and proving the data products that operations leaders act on every shift. On the Blue Bird RTLS Phase II engagement (Fort Valley, GA), the incumbent owns the onshore build and verification of the Digital Production Control Center (DPCC) and its supporting Power BI product family, working within the reference architecture established by the Senior RTLS Engineer (edge, KINEXON OS, and anchor grid) and the Senior Technical Fellow - Industry 4.0. The role translates KINEXON UWB Real-Time Location System (RTLS) event streams, VersaCall Digital Andon events, and Infor CloudSuite Automotive (CSA) ERP data into a governed Microsoft Fabric / OneLake medallion data estate (Bronze / Silver / Gold) and a trusted semantic layer. A defining responsibility of this position is onshore ownership of correctness: authoring precise, testable build specifications for offshore development partners, formally reviewing and accepting their deliverables, and validating that reported production metrics (Takt attainment, work-in-process position, dwell time, defects per unit, Andon response, and automated backflush) match observed reality on the assembly line. The incumbent works directly with Blue Bird operations, materials, quality, and information technology stakeholders, and contributes the reusable build patterns that will carry into subsequent line rollouts and future phases. Essential Functions & Responsibilities Builds, tests, and maintains the Digital Production Control Center (DPCC) and the supporting Power BI product family (Actual versus Plan and Takt attainment, Andon event and response analytics, WIP position and dwell time, defects per unit and first-pass quality, and material shortage and exception views) to C5MI visual design and performance standards. Develops and maintains the Microsoft Fabric / OneLake medallion data estate (Bronze / Silver / Gold), including ingestion of RTLS and Andon event streams, ERP master and transactional data, lakehouse and dimensional modeling, incremental refresh, and semantic models tuned for DAX and Direct Lake performance. Owns the governed semantic layer and KPI dictionary: a single documented definition of every published metric, with lineage traced from source event through to executive tile, so that operations, materials, quality, and finance work from one version of the truth. Authors detailed, testable build specifications for offshore development partners across the API, Infor, and Microsoft workstreams, including data contracts, transformation logic, edge cases, error handling, and expected results. Reviews, tests, and formally accepts or rejects offshore deliverables against those specifications; maintains the defect log, drives rework to closure, and escalates persistent quality or throughput issues to the Senior Technical Fellow. Performs onshore validation of delivered metrics against physical reality on the production line (timed observation at stations, comparison of system-reported dwell and Takt against direct measurement, and reconciliation of automated backflush against actual material consumption) and corrects logic wherever the two diverge. Translates the zone, geofence, and asset definitions established by the Senior RTLS Engineer into production semantics, including station entry and exit, dwell state, line position, and vehicle progression through the build sequence. Implements and tests data quality controls across the pipeline, including event completeness and latency monitoring, tag and anchor health checks, duplicate and out-of-sequence event handling, and post-cutover validation test cases. Leads requirements elicitation with client stakeholders (facilitated working sessions, Joint Application Development (JAD) sessions, gemba walks, and process mapping), converting operational pain points into prioritized, traceable, and testable reporting requirements. Delivers working sessions, system demonstrations, and readouts to client operations leadership and executive stakeholders, translating data and system behavior into operational and financial language appropriate to the audience. Implements access and governance controls for delivered data products, including Power BI row-level security, workspace and deployment pipeline management, service account handling, and adherence to customer data handling requirements, including any restrictions applicable to offshore development resources. Authors technical artifacts to C5MI standards, including data flow diagrams, interface documentation, data dictionaries, semantic model and report specifications, and acceptance test packages aligned with the C5MI Standard Operating Procedures (e.g., the C5MI-SOP-RTLS series). Supports commissioning, site acceptance testing, end-user training, and hypercare at customer facilities, including DPCC user adoption and first-line triage of reported issues. Contributes reusable report templates, semantic model patterns, and specification templates that reduce build cost and rework on subsequent line rollouts and future engagement phases. Engages constructively with C5MI's AI-augmented engineering workflows, applying approved internal AI tools to accelerate design, code generation, documentation, and review while validating all output for technical correctness, security, and quality. Adheres to all certified processes as part of our commitment to maintaining the highest standards of quality and information security, which includes actively participating in quality assurance activities and ensuring the protection of sensitive information in accordance with our security policies. Performs other related tasks as assigned by direct supervisor. Minimum Requirements: Bachelor's degree in Engineering, Computer Science, Information Systems, Data Analytics, Industrial Engineering, Economics, or a related quantitative or technical discipline; equivalent professional experience will be considered in lieu of a degree. Five (5) or more years of experience in data engineering, business intelligence, enterprise systems, or business analysis, including at least two (2) years delivering solutions within a manufacturing, distribution, or industrial operations environment. Demonstrated hands-on experience building operational and executive dashboards in Power BI (or comparable platforms such as Tableau, Looker, or Qlik Sense), including data modeling, KPI definition, visual design, and query performance optimization. Strong SQL capability (T-SQL, PL/SQL, or equivalent) and hands-on experience with cloud data platforms and warehouses (Microsoft Fabric, Azure Synapse or Databricks, Snowflake, Google BigQuery, or comparable), including ETL / ELT pipeline development. Demonstrated ERP experience (SAP, Infor, or comparable), including integration, master data, and the full data migration and validation lifecycle. Proficiency in at least one programming or scripting language for data work and automation (Python strongly preferred; R, PowerShell, or JavaScript / TypeScript acceptable), and familiarity with Git-based version control workflows. Demonstrated ability to author precise, testable technical specifications and acceptance criteria, and to formally validate delivered work against them. Proven requirements elicitation and process analysis capability: facilitated working sessions, JAD sessions, as-is / to-be process mapping, gap analysis, and traceable requirements documentation. Working knowledge of manufacturing operations concepts (Takt time, cycle time, work-in-process, throughput, first-pass yield, defects per unit, Andon and escalation, and production backflush), sufficient to build metrics that operations leaders will act on. Ability to present technical material and deliver live system demonstrations to client stakeholders, including operations leadership. Ability to work effectively in a professional services delivery model, including billable utilization targets, concurrent workstreams, and direct accountability to client sponsors. Willingness and ability to travel domestically up to fifty percent (50%), with sustained on-site presence at customer facilities (initially Fort Valley, GA) during active build, commissioning, and hypercare phases. US person status required (US citizen, lawful permanent resident, or other US person as defined under ITAR / EAR) due to potential assignment to Department of Defense engagements. Nice to Have: Experience specifying for, directing, or formally accepting the work of offshore or geographically distributed development teams, including written specification handoff, asynchronous review, and defect management. Specific Microsoft Fabric experience: Lakehouse and Warehouse, Data Factory pipelines, Notebooks and Spark, Direct Lake semantic models, deployment pipelines, and Microsoft Purview governance. Experience working with event-stream or time-series data (IoT, telemetry, sensor, or transactional event feeds) . click apply for full job details

Job Description Job Description CoreWeave is The Essential Cloud for AI . Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at . What You'll Do: The core compute team builds and operates the compute infrastructure that underpins all the AI workloads running on CoreWeave. We turn accelerated servers into reliable, isolated, API-addressable compute that customers can build on, and we keep it healthy and current for the life of their workloads. Everything above us depends on it: customers running training, inference, agents, and sandboxes directly on our compute, and internal teams building higher-level services, including CoreWeave Kubernetes Service (CKS), on top of our primitives. About the role: As Staff Product Manager for Core Compute, you'll be responsible for driving the roadmap and strategy for the compute layer that everything else at CoreWeave sits on: how compute gets allocated and delivered, how it stays healthy and current, and how it is isolated and made consumable through APIs that both external customers and internal teams build against. You will be working on the foundation of the compute stack to both evolve what already exists, and help define the next generation of compute services for AI. In this role, you will: Lead the product strategy, roadmap, and execution for CoreWeave's core compute services, including instance lifecycle, node images and system software currency, hardware health and remediation, tenancy and isolation, and the capacity and reservation semantics customers buy against Serve two customer sets at once: external customers consuming compute directly, and internal teams building higher-level services, including CKS, on the same primitives Partner with engineering, sales, finance, and marketing teams to ensure alignment on goals, product details, effective product launches, and seamless go-to-market execution Conduct in-depth market research and competitive analysis to identify current state, emerging trends, and opportunities for differentiation Partner with industry partners, marketing, and sales teams to develop and execute effective go-to-market strategies, including positioning, messaging, and competitive differentiation Define key metrics and establish robust reporting to monitor the performance of compute services, identify areas for improvement, and inform future decisions Who You Are: 8+ years of professional experience, with 5+ years in Product Management of cloud services or in the AI/ML market segment Deep understanding of cloud compute at the instance layer: how compute is provisioned, delivered, kept current, isolated, and reclaimed at scale Proven ability to lead cross functional teams, with strong decision-making, project management, and mentoring skills Demonstrated experience working closely with customers to identify needs and translate them into product features and solutions Excellent verbal and written communication skills with the ability to influence cross-functional teams and stakeholders Ability to think strategically while being able to dive into technical details to guide engineering teams Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field. MBA or equivalent experience is a plus Preferred: Hands on experience with a large-scale compute or instance service, such as EC2, Google Compute Engine, Azure Compute, or an equivalent internal provisioning platform Familiarity with accelerated compute, high-performance interconnect, and the behavior of large multi-node workloads Good grasp of the financial/economic dimensions of operating cloud compute services Wondering if you're a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams - even if you aren't a 100% skill or experience match. Here are a few qualities we've found compatible with our team. If some of this describes you, we'd love to talk. You love to build businesses as much as build products You're curious about where the next product opportunity is, and where the AI market is going You're an expert in the fundamentals of how computers work at scale, and the implications of distributed systems The base salary range for this role is $188,000 to $275,00. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). What We Offer The range we've posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location. In addition to a competitive salary, we offer a variety of benefits to support your needs. The benefits below reflect our US-based offerings for full-time employees; for roles in other locations, benefits vary and are shared during the hiring process. These include: Medical, dental, and vision insurance - 100% paid for by CoreWeave Company-paid Life Insurance Voluntary supplemental life insurance Short and long-term disability insurance Flexible Spending Account Health Savings Account Tuition Reimbursement Ability to Participate in Employee Stock Purchase Program (ESPP) Mental Wellness Benefits through Spring Health Family-Forming support provided by Carrot Paid Parental Leave Flexible, full-service childcare support with Kinside 401(k) with a generous employer match Flexible PTO Catered lunch each day in our office and data center locations A casual work environment A work culture focused on innovative disruption California Applicants California Consumer Privacy Act Equal Opportunity & Accommodations CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. As part of this commitment and consistent with the Americans with Disabilities Act (ADA) , CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: . Export Control Compliance This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. 1157, or (iv) asylee under 8 U.S.C. 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.

Job Description Job Description Company Description About AbbVie AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at . on LinkedIn, Facebook, Instagram, X and YouTube. Job Description While the AI innovation race in Biopharma is focused on Drug discovery, Product Development/ CMC represents the next barrier/ bottleneck. The complexity of biological systems, the rigor of regulatory expectations, the pace of pipeline growth, and the enormous value at stake make this one of the highest-leverage domains for applied data science and AI in the entire pharmaceutical value chain. We here at BTS - PDST, are building a dedicated, AI-native team that is driving cutting edge programs across early stage, late stage and commercial product development to accelerate E2E product development and launch, maximize yields of block buster products. Through our deep collaboration with PDST scientists we are boldly reimagining how Abbvie can bring our pipeline products and lifesaving drugs to patients faster, safer and in cost effective manner fueled by AI. Principal Data Engineer is a highly technical, AI-native role responsible for designing, building, and operating production-grade data pipelines and data products that power AI/ML, analytics, and automation across AbbVie's CMC and manufacturing ecosystem. This role is embedded inside PDST and works at the frontier of pharmaceutical data engineering. You will integrate and harmonize data from the full spectrum of manufacturing and development systems - including MES, historians, LIMS, QMS, ERP, and instrument platforms - and transform it into reliable, governed, semantically rich data assets that data scientists, process engineers, and AI systems can actually use. Enterprise-scale scope: Enterprise-scale biologics portfolio spanning clinical, commercial, and lifecycle stages Building AI playbook for the future: First-in-AbbVie and first-in-biologics analytical approaches; you build the AI playbook for the future Growth and Impact: Direct impact on regulatory submissions, commercial readiness, and manufacturing decisions through deep cross-functional exposure to manufacturing, quality, regulatory, and scientific leadership Mission: Every model you build helps ensure safe, reliable medicines reach patients at scale Responsibilities Data Ingestion & Integration Design and implement scalable, robust data ingestion pipelines that connect CMC and manufacturing source systems - including MES (Manufacturing Execution Systems), process historians, LIMS, QMS, ERP platforms, and instrument data sources - to centralized and federated data environments. Build connectors, adapters, and integration layers that handle the heterogeneous data formats, protocols, and latency profiles characteristic of pharmaceutical manufacturing environments. Support both batch and real-time/streaming data patterns, selecting appropriate architectures based on use case requirements. Data Harmonization & Semantic Modeling Develop and maintain harmonized data models and ontologies that bring consistency to CMC and manufacturing data across sites, systems, and modalities. Execute semantic mapping efforts that align source system fields, units, and identifiers to enterprise data standards and scientific meaning. Collaborate with process scientists, analytical chemists, and manufacturing engineers to ensure data models accurately reflect domain reality. Data Quality, Observability & Governance Implement automated data quality controls, validation frameworks, and anomaly detection mechanisms across pipeline layers. Build and maintain data lineage documentation and metadata infrastructure, enabling full traceability from source system to AI model input. Establish pipeline observability practices - monitoring, alerting, SLA tracking - to ensure data product reliability in production. Support data governance practices aligned with GxP requirements, 21 CFR Part 11, and AbbVie data standards. AI/ML Enablement & Data Product Development Architect and deliver governed, versioned, reusable data products purpose-built for AI/ML consumption, including feature stores, curated datasets, and vector-ready data layers for RAG and LLM applications. Partner closely with data scientists, ML engineers, and process modelers to understand model data requirements and translate them into reliable, scalable data infrastructure. Accelerate AI program delivery by eliminating data bottlenecks - not by workarounds, but by solving root causes structurally. Platform & Operational Enablement Contribute to the design and evolution of PDST's cloud-based data platform, including lakehouse architecture, data cataloging, access control, and compute infrastructure. Write and maintain infrastructure-as-code, CI/CD pipelines, and automated testing frameworks for data systems. Support platform onboarding of new CMC data domains and manufacturing sites, ensuring consistent application of standards and patterns. Provide operational support for production data pipelines, maintaining uptime and data freshness commitments. Stakeholder Engagement & Scientific Leadership Influence technical decision-making without formal authority - earning trust through scientific rigor, transparent methodology, and demonstrated business impact. Qualifications Required: Bachelor's Degree Computer Science, Data Engineering, Information Systems, Software Engineering, Bioinformatics, or a closely related technical field plus 6 years' experience; Master's Degree plus 5 years' experience; PhD plus 0 years' experience. Respective years of hands-on experience designing and building enterprise-grade data pipelines, integration workflows, and data products in complex, multi-source environments. Expert-level proficiency in Python for data engineering tasks - pipeline development, transformation logic, data validation, and automation. Strong SQL skills across modern analytical and transactional databases; comfort with both ANSI SQL and platform-specific dialects. Demonstrated experience with cloud data platforms (AWS, Azure, or GCP) and modern data stack components - including tools such as dbt, Spark, Airflow, Databricks, Snowflake, or equivalents. Develop ETL/ELT pipelines using tools such as Informatica, Talend, Apache NiFi, and cloud-native services (e.g., AWS Glue, Azure Data Factory). Implement master data management (MDM), metadata management, and data cataloging solutions to ensure proper data lineage, accessibility, and compliance. Set and enforce standards for API development and data integration (REST, GraphQL, OData), enabling seamless integration using microservices architectures. Ownership orientation: you define your own problem space, drive solutions to completion, and hold yourself accountable to outcomes - not just outputs. Solution-architect instinct: you think before you build, consider the full landscape of available approaches, and choose tools based on fit-for-purpose reasoning rather than familiarity or trend. Scientific integrity: you build models you can explain, defend, and improve - and you apply the same standard to the work of others. Influence through credibility: you earn the confidence of scientists, engineers, and quality professionals by being right, being clear, and being useful - not by title or volume. Bias for impact: you are drawn to problems where the stakes are high and the analytical opportunity is real, and you are energized rather than intimidated by ambiguity. Preferred: 3+ years of hands-on experience designing and building enterprise-grade data pipelines, integration workflows, and data products in complex, multi-source environments. Familiarity with technology transfer workflows, process characterization study design, or commercial process validation (PPQ/PV) in a biologics or pharmaceutical context. Experience in pharmaceutical, biotech, or other regulated life sciences manufacturing environments. Familiarity with GxP data principles, 21 CFR Part 11 compliance, or data integrity requirements in regulated industries. Prior exposure to manufacturing source systems such as MES, process historians (e.g., OSIsoft PI/AVEVA), LIMS, QMS, or ERP platforms Experience building data infrastructure for AI/ML programs - including feature engineering pipelines, model training datasets, or vector/embedding data layers for RAG architectures. Knowledge of biologics manufacturing processes (e.g., upstream cell culture, downstream purification, fill-finish) or CMC development workflows. Familiarity with data mesh, data fabric, or federated data architecture patterns. Experience with graph databases, knowledge graphs, or ontology frameworks applied to scientific or manufacturing data. Contributions to open-source data tooling or demonstrated engagement with the modern data engineering community. Design logical, physical, and conceptual data models using modeling tools (e.g., Erwin, PowerDesigner, dbt). . click apply for full job details