• Lead Data Engineer- Healthcare Interoperability • We are seeking an experienced Lead Data Engineer to join our healthcare technology team with a primary focus on healthcare interoperability. • This role will be instrumental in designing, building, and maintaining our Azure-based data infrastructure, including databases, data pipelines, analytics platforms, and business intelligence solutions — with an emphasis on integrating with Electronic Health Record (EHR) systems and healthcare data exchange standards (FHIR, C-CDA, HL7). • The ideal candidate will have deep expertise in the Microsoft data stack, strong architectural thinking, and experience with healthcare data compliance requirements. • This senior-level position will also provide technical leadership, mentorship to the broader engineering team and reports to the Director of Data Engineering. • Design and implement scalable, secure data architectures on Azure to support business intelligence, analytics, and operational systems • Build and maintain data pipelines using Azure Data Factory, Azure Synapse and related services • Contribute to database designs across multiple platforms (Azure SQL Database, SQL Managed Instance, PostgreSQL, CosmosDB) • Optimize data storage strategies across Azure Blob Storage, Data Lake, and structured databases • Design data models and structures that enable efficient analytics and reporting • Design, develop, and maintain complex stored procedures, functions, triggers, and views • Implement database DevOps processes including schema versioning, deployment automation, and rollback procedures • Perform database performance tuning, indexing strategies, and query optimization • Ensure data integrity, security, and compliance with HIPAA/HITRUST requirements for PHI data • Manage database lifecycle across development, pre-production, and production environments utilizing RedGate Flyway • Design and implement ETL/ELT processes to integrate data from multiple sources • Build event-driven data processing solutions including message producers, consumers, and workers using Azure Service Bus, Event Grid, and related messaging services • Integrate with external REST APIs for data ingestion and develop internal data APIs using Python (FastAPI/Flask) on Azure Container Apps or Functions • Develop data transformation logic and orchestration workflows • Ensure data quality, consistency, and lineage across the data platform • Integrate with Azure AI services and machine learning endpoints as needed • Review designs of Power BI solutions including semantic models, reports, & dashboards • Collaborate with stakeholders to translate business requirements into technical solutions • Optimize data structures for reporting and analytics performance • Provide technical guidance and mentorship to junior developers and engineers • Contribute to data engineering best practices, standards, and patterns • Participate in architecture reviews and technical decision-making • Collaborate with DevOps and Infrastructure teams on platform improvements • Drive continuous improvement in data quality, performance, and reliability • Create and maintain comprehensive technical documentation including data dictionaries, architecture diagrams, and process flows • Document data lineage, transformation logic, and business rules • Ensure all data handling practices meet HIPAA/HITRUST compliance requirements • Maintain audit trails and documentation for compliance purposes • Troubleshoot and resolve complex data-related issues across the platform • Provide escalation support for production incidents • Collaborate with cross-functional teams to support business operations • Participate in on-call rotation as needed

• Lead planning, execution, and delivery of data management and data engineering projects supporting OHS program oversight and operations. • Apply iterative and flexible project management approaches to prioritize work based on value, user needs, and level of effort. • Coordinate closely with the Project Manager to align data project priorities with contract deliverables and performance metrics. • Supervise and provide technical direction to data-focused staff, including Data Analysts, Data Visualization Specialists, Data Management Specialists, and Data Entry Support Specialists. • Design, build, and maintain data pipelines, integrations, and automation processes using federally compliant tools and platforms. • Support integration of data from federal systems such as HSES, AMS, GrantSolutions, and the TTA Hub into operational and analytical tools. • Maintain and enhance workflow and task tracking solutions, including Smartsheet-based tools (e.g., SmartFlow). • Support the use of the OHS Data Layer and cloud-based infrastructure to enable scalable, secure data processing and analysis. • Ensure data accuracy, integrity, and alignment across systems, mitigating competing sources of truth. • Implement and support data quality assurance, validation processes, and governance practices appropriate for federal environments. • Ensure documentation of data structures, pipelines, and processes to support knowledge transfer and continuity. • Lead development of data products, dashboards, reports, and automated outputs that support grants management, monitoring, and leadership decision-making. • Support generation of standardized documents and correspondence through automated data integration where appropriate. • Enable data-informed decision-making through improved access to timely, relevant, and well-structured data. • Analyze data workflows and business processes to identify opportunities for efficiency, automation, and improvement. • Develop and maintain technical documentation, data dictionaries, process documentation, and handoff materials. • Support the development of training materials and guidance to promote consistent use of data tools and solutions. • Respond to data-related inquiries and support ad hoc and recurring data requests from OHS staff and leadership. • Participate in briefings, meetings, and planning sessions related to data management initiatives. • Support coordination across technical and programmatic teams to ensure solutions align with operational needs.

• Lead end-to-end data migration from legacy systems to cloud platforms, including data mapping, transformation, and validation (Salesforce-centric). • Analyze and convert unstructured, document-heavy data into structured, analytics-ready formats using Document AI. • Implement data quality processes (cleansing, deduplication, reconciliation) to ensure accuracy and completeness post-migration. • Support phased migration and system cutover with minimal operational disruption. • Design, build, and maintain MuleSoft integrations, including API development for real-time and batch data exchange. • Apply data transformation logic (e.g., DataWeave) and troubleshoot integration/data flow issues across systems. • Contribute to Salesforce Data 360 implementation, including data harmonization, identity resolution, and unified profiles. • Ensure proper data ingestion, lineage, metadata management, and traceability across the ecosystem. • Ensure compliance with data governance, privacy, and security requirements (e.g., PII). • Collaborate in Agile teams; support testing, documentation, and audit readiness across migration and integration efforts.

• Design and build the AWS-native data foundation behind enterprise AI applications • Lead the design and evolution of the knowledge graphs and ontologies powering AI's reasoning, retrieval, and explainability • Align enterprise data into a coherent, queryable graph with clear provenance across structured, semi-structured, and unstructured sources • Curate grounding corpora, eval datasets, and retrieval benchmarks for LLM-based features • Build ingestion and transformation pipelines in Python and SQL using AWS services • Author infrastructure as code in CloudFormation and apply AWS best practices • Partner with security and platform teams to integrate data access with enterprise identity and access policies • Set the design direction for data and semantic modeling across the team