Data Engineer
Company: JANUS Research Group
Location: Fort Bliss, TX (Remote)
Type: Full-time
Level: mid
Remote: Yes
Posted: 2026-02-27
About this role
Location:
Fort Bliss, TX (routine CONUS travel; OCONUS as mission dictates) or Remote (preference for Ft. Eustis, VA or Austin, TX)
Clearance:
Active Secret
About The Role
Join JANUS as a
Data Engineer
supporting Army modernization. You will design and operate secure, scalable data pipelines that integrate operational, simulation, and enterprise data into analysis-ready formats. Your work will enable
real-time dashboards, predictive analytics, and decision support products
used across Army event cycles and campaign planning.
Key Responsibilities
- Build & Operate Pipelines: Design, implement, and optimize ETL/ELT pipelines using SQL, Python, and Azure services (Data & Storage, Databricks, Purview).
- Integrate Data Sources: Ingest and standardize diverse Army datasets into relational databases with clear lineage, metadata, and quality controls.
- Support Army Operations: Enable near-real-time data products that inform analytics, dashboards, and assessments supporting Army staff and decision-makers.
- Cloud Engineering: Leverage Azure PaaS solutions to design scalable, secure data integration strategies aligned with AIMD’s enterprise architecture.
- Governance & Security: Apply OPSEC, IA, and PII safeguards across workflows; ensure compliance with Army data governance practices.
- Collaboration: Work with software development teams, stakeholders, and analysts to ensure data solutions meet mission requirements and PRS-driven timelines.
Qualifications
- Education: Bachelor’s degree in Computer Science, Information Systems, Engineering, Math, or related field. Equivalent experience may substitute.
- Clearance: Active Secret clearance required.
- Experience:
- 3–5+ years in data engineering, ETL, or data wrangling.
- Hands-on SQL and scripting/ETL (Python or similar).
- Experience with Azure cloud services (Data & Storage, Analytics, Databricks, Purview) preferred.
- Familiarity with DoD/Army datasets, event-driven ...