> Markdown version of [/jobs/ext/2165639-data-engineer-databricks-engineer](https://www.wearedevelopers.com/jobs/ext/2165639-data-engineer-databricks-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer / Databricks Engineer - **Company:** A.N.G. USA Inc. - **Location:** Joint Base Andrews, MD, United States (Remote available) - **Experience:** Expert - **Salary:** $125,000.0 - $178,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Microsoft Azure, Cloud Computing, Configuration Management, Software Documentation, Databases, Continuous Delivery, Continuous Integration, Data Governance, Extract Transform Load (ETL), Data Transformation, Dataspaces, Data Warehousing, Python (Programming Language), Network Information Services, Performance Tuning, Query Optimization, Power BI, SQL Databases, Data Streaming, Systems Integration, Tableau (Software), Data Logging, Scripting, Sql Optimization, Apache Spark, Test Scripts, Indexer, Git, SC Clearance, Data Lakes, Information Technology, Real Time Data, Data Management, Multiplatform, Software Version Control, Data Pipelines, Databricks - **Published:** August 21, 2026 - **Apply:** https://www.careerbuilder.com/job-details/data-engineer-databricks-engineer-senior-andrews-air-force-base-md--4bfb1728-89c1-45c9-849e-861e798f3f81 ## About the Role * Demonstrated hands-on experience developing production-grade ETL/ELT pipelines using Azure Databricks or comparable Spark-based data platforms. * Advanced SQL and Python skills for data transformation, validation, automation, troubleshooting, and performance optimization. * Experience with batch and streaming ingestion, APIs, schema management, orchestration, monitoring, data quality, and failure recovery. * Experience with Git-based version control and CI/CD practices for data-engineering solutions. * Knowledge of data warehousing/lakehouse patterns, indexing/query optimization, access control, encryption, and secure handling of sensitive/CUI data. * Must satisfy applicable DoD/DAF security, cybersecurity-awareness, CUI, OPSEC, and access-training requirements. Preferred Qualifications * Experience extracting and transforming data from DAF/DoD systems such as MILPDS, DCPDS, AFRISS, CHRIS, CMS, CRIS, GFEBS, DEAMS, REMIS, AROWS, M4S, iEMS, or Lockheed Martin Tableau. * Experience integrating Databricks workloads with Palantir Foundry, Microsoft Azure, Advana/WDP, Power BI, or AskSage., Access Control, Application Programming Interface (API), Artificial Intelligence (AI), Automation, Business Intelligence Software, Cloud Computing, Content Management Systems (CMS), Continuous Deployment/Delivery, Continuous Integration, Cryptography, Data Lake, Data Management, Data Quality, Data Warehousing, Database Extract Transform and Load (ETL), Documentation, Ecosystems, Error Handling, Git, Government, Government Contracts, Identify Issues, Microsoft Windows Azure, Multiplatform/Cross-Platform, NIS (Network Information Service), Performance Tuning/Optimization, Power BI, Python Programming/Scripting Language, Quality Monitoring, Query Optimization, Reconciliation, Root Cause Analysis, SQL (Structured Query Language), Sales Pipeline, Secret Clearance, Security Clearance, Source Code/Configuration Management (SCM), Tableau, Technical Support, Technical Writing, Test Scripts, Testing, United States Department of Defense (DoD), User Documentation, Work From Home ## Description Position SummaryNationwide IT Services, NIS, is seeking a Senior Data Engineer / Databricks Engineer to design, build, test, deploy, optimize, and sustain enterprise data pipelines supporting the ANG CDAO data ecosystem for a potential opportunity. The engineer will work primarily with Azure Databricks, SQL, Python, Git-based CI/CD, and integrated DoD/DAF/ANG source systems to provide reliable ingestion, transformation, orchestration, data quality, monitoring, and technical documentation., * Design, build, test, deploy, and maintain automated and manual ETL/ELT pipelines supporting approximately 15-20 DAF, ANG, and DoD source systems. * Implement ingestion patterns for structured, unstructured, API, batch, and streaming data; support near-real-time data currency requirements where applicable. * Develop SQL and Python transformation logic to cleanse, standardize, deduplicate, validate, and enrich enterprise data in accordance with CDAO data standards and business rules. * Build and operate Azure Databricks jobs, orchestration sequences, triggers, and workload schedules while optimizing execution performance and cloud-compute utilization. * Implement automated data-quality checks, reconciliation controls, invalid-record quarantine, monitoring, logging, alerting, and recoverable error-handling patterns. * Triage critical pipeline failures, perform root-cause analysis, and restore service within required response windows. * Maintain pipeline code, configuration, infrastructure/deployment scripts, and test assets in the official Git repository and execute automated CI/CD build and security testing before release. * Create and maintain data lineage, source-to-target mappings, architecture documentation, operational runbooks, and quarterly technical-documentation updates. * Support data warehouse/lake administration, query optimization, Power BI dataflows, and secure cross-platform data movement as needed. ## Related Videos - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Optimizing Discovery: PostgreSQL's Role in Transforming GetYourGuide's Search](https://www.wearedevelopers.com/videos/1647-optimizing-discovery-postgresql-s-role-in-transforming-getyourguide-s-search) - [Beyond Dashboards: Fixing Text-to-SQL with Semantic RAG](https://www.wearedevelopers.com/videos/2036-beyond-dashboards-fixing-text-to-sql-with-semantic-rag) - [Data Analytics with Microsoft Fabric: End-to-End Use Case with Data Agents](https://www.wearedevelopers.com/videos/1547-data-analytics-with-microsoft-fabric-end-to-end-use-case-with-data-agents) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Dev Digest 132 - Binging WADFlix?](https://www.wearedevelopers.com/magazine/473-dev-digest-132-binging-wadflix) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)