Role Description GDIT is looking to hire a Sr. Data Engineer Principal. The qualified individual architects and implements high-throughput, low-latency data pipelines. This position provides critical technical expertise in support of Special Operations Forces (SOF). You will help design and implement cutting-edge, data-driven systems that collect, interpret, and report performance information on high-performance vehicles and their sub-systems. Your work will enable advanced insight into logistics, operational performance, predictive maintenance, and lifecycle extension for these mission-essential platforms. This is an opportunity to directly support the Nation’s most elite forces—bringing your technical talent to bear on real-world challenges that matter. Qualifications - MS with 10+ years data engineering experience. - Strong SQL tuning and distributed compute expertise. - Security clearance level: Must be able to obtain Secret clearance. - Preferred: Experience with time-series databases or tactical edge systems. Requirements - Suggested Technical Stack: - Python, Scala, SQL. - Streaming: Kafka, Flink, Spark. - Orchestration: Airflow, Dagster, Prefect. - Storage: Delta Lake, Iceberg, Snowflake. - Quality: Great Expectations, OpenMetadata. Benefits - Growth: AI-powered career tool that identifies career steps and learning opportunities. - Support: An internal mobility team focused on helping you achieve your career goals. - Rewards: Comprehensive benefits and wellness packages, 401K with company match, and competitive pay and paid time off. - Flexibility: Full-flex work week to own your priorities at work and at home. - Community: Award-winning culture of innovation and a military-friendly workplace. Company Description We are GDIT. A global technology and professional services company that delivers consulting, technology and mission services to every major agency across the U.S. government, defense and intelligence community. Our 30,000 experts extract the power of technology to create immediate value and deliver solutions at the edge of innovation. We operate across 50 countries worldwide, offering leading capabilities in digital modernization, AI/ML, Cloud, Cyber and application development. Together with our clients, we strive to create a safer, smarter world by harnessing the power of deep expertise and advanced technology.

• Create innovative solutions for handling peta-bytes of data with billions of rows & joins • Program and maintain our data pipelines that fuels our on-premise/cloud data warehouse used to generate and serve our models • Maintain and improve our fleet of data servers (the software), making sure they are reliable and able to process our billions of logs and data points • Develop and productionize data pipelines for our ML models in both bare-metal and the cloud environment • Make suggestions and lead projects to improve our data processing capabilities • Contribute to the team enabling us to be always better

• Partner with the engineering team to lead the knowledge transfer of "Atlas" (built in Python), taking full architectural ownership and ensuring its continued health and progression. • Using Apache Airflow to manage and optimize the daily ingestion of analytics from multiple disparate sources (social media, podcast platforms, etc.) to ensure a clean, reliable, and "healthy" data stream. • Act as a "data detective" to identify what information we are missing and prioritize new data collection that aligns with our financial stability and growth levers. • Build and maintain intuitive dashboards (e.g., Power BI or custom builds) that allow non-technical peers to answer basic everyday questions without needing manual engineering support. • Transform raw data into structured, "customer-ready" packages to support our heavy push into data licensing. • Utilize your knowledge of the media analytics landscape to guide the organization on whether to build custom internal tools or leverage existing 3rd-party social media analytics solutions.

• Architect production-grade data pipelines that integrate clinical data through multiple channels—direct EHR connections (e.g., Epic, Cerner, Athenahealth), health information exchanges (HIEs), health alliance networks, and third-party integration vendors—via FHIR R4 APIs, HL7v2 feeds, CCDA documents, and bulk data exports, while enforcing healthcare standards and clinical terminologies (ICD-10, SNOMED CT, LOINC, RxNorm), targeting sub-hour latency from clinical event to actionable insight and ≥99.9% pipeline reliability. • Lead end-to-end integration efforts with health plan partners, HIEs, health alliance networks, provider organizations, and data integration vendors—owning partner technical evaluation, connectivity, data mapping, validation, and production rollout. • Build and optimize cloud-native data infrastructure (AWS) and ETL/ELT workflows using modern orchestration tools (e.g., Step Functions, dbt) with robust data quality monitoring and lineage tracking. • Develop reusable backend frameworks, libraries, and internal tooling that accelerate onboarding of new data sources—whether direct EHR feeds, HIE connections, or vendor integrations—with the goal of reducing new-partner integration time by 50% or more while improving developer productivity and reducing operational toil across engineering. • Partner with data science and data analytics teams to build and operationalize the data foundations for predictive risk scores, care gap identification, clinical alerting, and patient outreach prioritization. • Collaborate with product and clinical teams to translate care delivery requirements into scalable, production-grade technical solutions and influence. • Ensure all data systems comply with HIPAA, HITECH, and applicable privacy regulations, implementing access controls, audit logging, encryption, and de-identification processes for PHI. • Provide technical leadership and mentorship to engineers across Waymark, raising the bar on healthcare data best practices.