• The Mid-Level Full Stack Data Engineer is responsible for building and supporting data-driven features across backend services and thick client desktop applications. • Develop and maintain data ingestion and transformation pipelines. • Implement backend logic to process, validate, and analyze structured and semi-structured data. • Contribute to RESTful API development and service-layer integrations. • Support integration of processed data into thick client desktop applications (e.g., Electron-based platforms). • Assist in database schema design, data modeling, and query optimization. • Develop UI-integrated data features such as dashboards, validation results, and analytics views. • Write unit and integration tests to validate data processing logic. • Participate in sprint planning, backlog refinement, and demos. • Collaborate with senior engineers and architects to implement scalable and maintainable data solutions.

• Design and implement enterprise data architectures including Data Lakes, Data Warehouses, Data Fabric, and MDM solutions. • Build scalable data pipelines and data integration frameworks. • Define data governance, quality, lineage, and security standards. • Enable AI/ML initiatives through robust data engineering and architecture practices. • Collaborate with business and technology teams to develop data strategies and roadmaps. • Optimize data platforms for performance, scalability, and reliability.

• Participation and representation in a client facing Data Governance Committee, including making recommendations, guiding decisions and recommendations within the scope of Client, State and Federal data governance policies, practices, and standards relevant to data management • Ensure and maintain to the highest standards the quality and security of data within program engagement through adherence to processes and procedures for access controls and monitoring of data activities and use to protect data integrity, including ensuring compliance for the preservation and protection of Protected Health Information (PHI) and Protected Identification Information (PII) • Collaborate with stakeholders in the design, testing, implementation and ongoing maintenance and support activities of data services • Assist the Client in solving data-related issues by managing data corruption or mapping data between program areas • Maintain internally established data quality reporting metrics, evaluate, and identify issues/corrections and coordinate and implement data management best practices • Identify data assets, lineage, and business rules within data domains to ensure data element continuity and avoid data conflict • Manage data design, creation and management of database architecture and data repositories • Maintain accurate and current content within the data management plan including all diagrams, workflows, and all other data related documentation • Conduct and comply with data reviews and auditing to ensure adherence to current standards, policies and design of the database architecture and repositories • Ensure documentation and processes are followed, including Architectural Board approvals and other necessary approvals, for all data architecture changes

• Design and operate the cloud data infrastructure powering AI initiatives. • Architect production-scale data lakes on AWS. • Build real-time ingestion and observability pipelines. • Own the vector search and embedding layers that feed RAG systems and autonomous agents.