5 jobs found

Job Description W2 only option, we cannot consider 1099 or C2C candidates Role Overview We are looking for an ETL Developer who is passionate about data integration, healthcare data transformation, and building reliable data pipelines that support client implementations. In this role, you will design, develop, and maintain ETL processes that move and transform data between client systems and our healthcare platform. This is a hands-on individual contributor role. You will work closely with implementation consultants, product teams, and client stakeholders to ensure data is delivered accurately, securely, and on schedule. If you enjoy solving complex data challenges, have strong SQL and ETL skills, and want to help healthcare organizations improve operational outcomes through technology, this role is a great fit. What You'll Do Data Integration & ETL Development Design, develop, and maintain ETL workflows to support new client implementations and ongoing production operations. Build scalable processes for extracting, transforming, validating, and loading healthcare data. Create reusable components and mapping frameworks that improve implementation efficiency. Troubleshoot and resolve data integration issues across multiple client environments. Data Quality & Validation Analyze source data and identify data quality concerns proactively. Implement validation rules and reconciliation processes to ensure data accuracy and completeness. Perform root cause analysis on data discrepancies and provide resolution recommendations. Collaborate with QA and implementation teams to support testing activities. Client Implementations Work directly with implementation teams to understand client-specific business and data requirements. Translate business mapping documents into technical ETL specifications. Support go-live activities and post-implementation stabilization efforts. Provide technical guidance during data conversion and migration activities. Collaboration & Continuous Improvement Partner with application developers, database administrators, and project teams throughout implementation projects. Participate in design reviews and technical discussions. Contribute to documentation, standards, and best practices. Identify opportunities to improve automation, monitoring, and operational efficiency. What You Will Bring ETL & Data Integration Foundations (Must Have) Strong hands-on experience developing ETL processes using enterprise ETL tools or custom frameworks. Advanced SQL skills with experience querying, transforming, and validating large datasets. Experience working with relational databases such as SQL Server, PostgreSQL, Oracle, or MySQL. Understanding of data mapping, transformation logic, and reconciliation processes. Data Management Skills (Must Have) Experience analyzing and troubleshooting complex data issues. Knowledge of data warehousing concepts and dimensional modeling. Ability to optimize ETL jobs for performance and scalability. Healthcare Data Experience (Preferred) Experience with healthcare data standards such as HL7, FHIR, EDI, or claims data. Familiarity with member, provider, clinical, or care management datasets. Understanding of HIPAA and healthcare data security requirements. Communication & Collaboration Strong verbal and written communication skills. Ability to explain technical concepts to non-technical stakeholders. Strong problem-solving and analytical thinking skills. Proven ability to manage multiple priorities in a client-facing environment. Engineering Ecosystem (Good to Have) Experience with Azure Data Factory, SSIS, Informatica, Talend, or similar tools. Exposure to cloud-based data platforms. Familiarity with CI/CD practices and source control tools such as Git. Qualifications B.E. / B.Tech / M.Tech in Computer Science, Information Technology, Engineering, or related discipline. 5+ years of ETL development and data integration experience. Experience supporting enterprise software implementations preferred. Primary Technologies ETL Tools : SSIS, Azure Data Factory, Informatica, Talend, or equivalent Databases : SQL Server, PostgreSQL, Oracle, MySQL Data Formats : CSV, XML, JSON APIs & Integration: REST APIs, Web Services Source Control : Git, Azure DevOps Healthcare Standards (Preferred): HL7, FHIR, EDI

Job Description Job Title: LoanIQ Application Support Engineer Location: Jersey City NJ Job description Job Summary We are looking for an experienced LoanIQ Production Support Lead to lead endtoend production support incident management and operational stability for the LoanIQ platform and its integrated ecosystem The ideal candidate should have strong handson LoanIQ support experience excellent troubleshooting capabilities and solid technical exposure across NET Oracle SQL Server J2EE UNIX Informatica MQ Mule and OpenShift The role requires strong experience in highseverity incident management root cause analysis monitoring release support and continuous service improvement Key Responsibilities Lead endtoend LoanIQ production support and maintain overall platform stability Manage highseverity incidents service restoration escalations and problem followups Troubleshoot LoanIQ batch processing job failures feeds files and integration issues Investigate upstream and downstream applicationinterface failures Proactively monitor production health and identify potential operational risks Analyze business impact and recommend appropriate risk mitigation and preventive actions Use Splunk and Dynatrace for monitoring troubleshooting log analysis and performance investigation Support LoanIQ releases upgrades implementations infrastructure changes and production deployments Troubleshoot application and platform issues across NET Oracle SQL Server J2EE UNIX Informatica MQ Mule and OpenShift Perform root cause analysis RCA for recurring and critical production issues Maintain support runbooks operational procedures knownerror documentation defects and workarounds Provide timely incident status and escalation communication to business and technology stakeholders Partner with business CIO infrastructure vendor engineering and platform teams Participate in oncall support for critical incidents weekend deployments infrastructure changes disaster recovery exercises and industry testing Drive continuous improvement automation operational resilience and service stability Required Skills Proven years of experience in application development andor production support Strong handson experience supporting the LoanIQ platform in production Strong experience in L2L3 Production Support and Incident Management Experience handling P1P2 or highseverity production incidents and service restoration Strong troubleshooting experience involving batch jobs feeds files interfaces and integrations Technical knowledge of NET Oracle SQL Server J2EE UNIX Informatica MQ Mule and OpenShift Strong understanding of application monitoring log analysis and production health monitoring Experience with root cause analysis problem management and operational risk management Experience supporting production releases deployments upgrades and environment changes Strong stakeholder management communication and documentation skills Ability to participate in an oncall and afterhours production support rotation Desired Skills Strong experience with Splunk and Dynatrace Knowledge of ITSM ITIL processes including Incident Problem and Change Management Experience supporting complex financial or banking applications Exposure to disaster recovery and business continuity exercises Experience working with infrastructure middleware database product and vendor teams Primary Skills LoanIQ Production Application Support Incident Problem Management UNIX Oracle SQL Server NET J2EE Informatica MQ Mule OpenShift Splunk Dynatrace RCA BatchJob Support Skills Mandatory Skills : Dynatrace, MySQL, Oracle Linux Administration, Splunk Good to Have Skills : Critical Incident Response, Major incident management We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, citizenship status, age, disability, genetic information, protected veteran status, or any other characteristic protected by applicable law. verify.gov/sites/default/files/everify/posters/IER_RighttoWorkPoster.pdf

Job Description Responsible for developing complex requirements, enhancing, modifying and/or maintaining applications in the Financial Crimes technology to accomplish business goals. Software developers design, code, test, debug and document programs as well as support activities for the maintaining the application. Work closely with business partners in defining requirements for system applications. Typically requires 10+ years of applicable experience. Utilizes in-depth knowledge of business requirements, business environments, and technological alternatives to recommend innovations that enhance and/or provide a competitive advantage to the organization. Responsible for providing insight and direction from a data perspective, assessment of impact on technology systems and participation in the full development lifecycle of the capability being delivered. Contribute to story refinement/defining requirements. Estimate work necessary to realize a story/requirement through the delivery lifecycle. Perform proof of concept as necessary to mitigate risk or implement new ideas. Setup and automate continuous integration/continuous delivery pipeline. Working closely with Production Support teams, Platform teams and Business Partners, this person handles technical aspects of the application, including Change Management, Maintenance, Platform Upgrades, and Changes to requirements from both upstream and downstream interfacing applications. Demonstrated data sourcing, data analysis and modeling skills with the ability to build innovative data provisioning models to support large scale financial crimes data sourcing initiatives. Work with a team of Data Analysts and Developers related to Data to ensure best practice and governance is followed. Promoting and applying best practices and standards at a project, program level. Partners with the business to develop plans, including ongoing success measures, to sustain the change. Accountable for analyzing present-state, developing alternative future-state approaches and facilitating implementation. Effectively communicates with managers, peers and business partners on deliverables and timelines. Responsible for being Agile and following agile practice. In parallel, ensuring all Enterprise Change Standards are met. Experience in Teradata 16.x , SQL/BTEQ scripting, TPT, Informatica 10.x UNIX Shell scripting, Autosys, Cloudera CDP, Hadoop (Hive, Impala, PySpark, Scala) and Data analysis. Strong Data sourcing, data modelling and provisioning skills as related to support large scale AML monitoring and surveillance data assets. Database -Executed database intensive development, data migrations and conversions. Knowledge and experience working with SQL performance tuning. A person who can handle all at once - Design/Build, Hands-on development, Co-ordination of development in distributed environment Very good at engaging Business stakeholders and apt at Business engagement and requirement discovery Good experience in SDLC, Agile, Continuous Integration Continuous Delivery, and change management (CICD ) - Jira, Bitbucket,Jenkins, Artifactory, Ansible Good knowledge of Unix and development of shell scripts is required Good to have business knowledge in financial domains related to Anti-Money Laundering and Financial Crimes Effective communication and listening skills Software development in Agile environment. Education: BS/MS in Computer Science, Engineering, or any quantitative discipline

Job Description Senior PolyPaths Consultant & L3 Support Lead About the role Arrayo builds and embeds senior delivery teams inside the risk and technology functions of major financial institutions. We're hiring a Senior PolyPaths Consultant & L3 Support Lead to support a fixed income risk platform, with a particular focus on mortgage products. You'll combine deep PolyPaths expertise with ownership of production support and hands-on data engineering. The work spans daily risk runs, complex incident resolution, platform configuration, and the pipelines and automation that connect PolyPaths to the broader risk environment. This role calls for someone who can get productive quickly, take responsibility for critical production processes, and work confidently with Market Risk, Quant, Front Office and technology stakeholders. What you'll do Serve as the PolyPaths subject matter expert across configuration, scenario setup, batch processing, and integration with upstream and downstream systems. Support mortgage and securitized product analytics across agency MBS, CMOs, TBAs, non-agency RMBS, CMBS and ABS, including prepayment and default assumptions, OAS, duration, convexity and key rate sensitivities. Own L3 production support: investigate complex incidents, identify root causes, implement permanent fixes, and protect service levels for daily and intraday risk runs. Lead post-incident reviews, maintain runbooks, mentor L1/L2 support analysts, and participate in the on-call rotation. Write and optimize SQL to validate and reconcile trades, positions, market data and risk results. Develop and maintain ETL workflows using SSIS or equivalent tooling, and build Databricks pipelines and notebooks using PySpark and SQL. Use Python to automate batch processes, monitoring, data validation, reconciliation and exception reporting. Support PolyPaths upgrades and model assumption changes through regression testing, UAT and release planning, coordinating with the vendor on defects and enhancements. Document systems, processes and fixes to support audit and control requirements, and transfer knowledge to permanent teams. What we're looking for At least five years of hands-on PolyPaths experience across configuration, analytics, integration or production support. Strong fixed income risk knowledge, particularly mortgage products, prepayment modeling and OAS analytics. Proven experience providing or leading L3 support in financial services, including incident, problem and change management. Strong Python skills, with experience developing production-quality scripts for automation, data processing and validation. Advanced SQL skills, including complex queries, performance tuning and stored procedures. Hands-on experience with SSIS or another enterprise ETL platform, such as Informatica, Talend, Azure Data Factory or DataStage. Practical Databricks experience, including Spark, Delta Lake, notebooks and job orchestration. Working knowledge of market risk measures, including sensitivities, VaR, scenario and stress analysis, and P&L explain. Strong troubleshooting skills, clear communication, and the ability to work effectively under pressure around critical risk deadlines. Experience with other analytics platforms such as Bloomberg, Yield Book, Intex or Aladdin; workflow schedulers; CI/CD tooling; cloud platforms; or regulatory frameworks such as FRTB and CCAR/DFAST would be a plus. Why Arrayo You'll join a firm of senior practitioners working across risk, data and technology at leading financial institutions. This engagement offers direct ownership of a critical risk platform, close collaboration with business and technical teams, and the opportunity to improve both production reliability and the underlying data processes.

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