Note: The job is a remote job and is open to candidates in USA. Leidos is a leading company in the health and services sector, seeking a Cloud Database Engineer to develop secure and high-performing data solutions for the Navy. The role involves designing and building a maintainable data platform that processes and analyzes data to provide insights into warfighter readiness.
Responsibilities
- Build a production data platform on Advana (Databricks + S3 medallion architecture) that supports current and future studies
- Deliver a system the team can maintain and extend independently after handoff — particularly the ability to onboard new wearable vendors using a documented, repeatable pattern. Build iteratively and live, with the lab using each feature or pipeline as it is ready
- Engage hands-on with our existing data and stakeholders to propose and iterate on a medallion architecture (bronze/silver/gold), naming conventions, partitioning, and schema-evolution strategy. Bronze layer shall preserve raw, unmutated vendor payloads as a hard requirement. After major pipeline updates, either all downstream silver/gold data shall be regenerated, or a separate tracking table (or tables) shall document the pipeline version applied to each piece of data from raw onward
- Build pipelines (PySpark / Databricks-native tooling, contractor's choice) that trigger on landing of new files in the bronze bucket from Jupiter-managed vendor ingests, manual uploads, and other sources. Vendors in scope include Whoop, Oura, Garmin, Somfit, and Qualtrics
- Implement automated QC checks and reports as a standing part of every pipeline, so vendor-side breakages or anomalies (beyond simple type checks) are caught early and surfaced to the lab. QC shall include statistical checks of the data (e.g., distributional shifts, unexpected gaps, out-of-range values) in addition to structural and type checks
- Produce and demonstrate a documented, repeatable pattern for onboarding new wearable vendors. The pattern's adequacy will be judged by its successful application to the in-scope vendors
- Integrate historical data with input from the team and other SMEs
- Ensure gold-layer tables are structured for downstream consumption by Qlik Sense dashboards and Databricks notebooks (including future ML/LLM use cases)
- Maintain living documentation (architecture, data model, vendor onboarding playbook, operational runbook) throughout. Conduct working knowledge-transfer sessions with staff over the course of the cloud pipeline development
- Weekly or bi-weekly syncs with lab technical staff; demos at meaningful milestones rather than fixed calendar dates
- Coordinate with the Navy Jupiter/Advana team where pipelines depend on Jupiter managed vendor ingests
Skills
- Requires BS degree and 8 – 12 years of prior relevant experience or Masters with 6 – 10 years of prior relevant experience. May possess a Doctorate in technical domain
- Must possess or be able to obtain an active Secret Security Clearance. US Citizenship is required
- Requires expert knowledge of and ability to apply advanced technical principles, theories, and concepts
- Familiarity with the Advana ecosystem and Jupiter-managed data ingest frameworks
- Prior experience engineering data pipelines
- Able to develop solutions to complex technical issues and problems that impact multiple area or disciplines
- Prior experience engineering data pipelines specifically for commercial wearable devices (Oura, Whoop, Garmin) or survey platforms (Qualtrics)
- Experience working with military health research
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