U.S. Department of Veterans Affairs
10,000+ employees
Founded 1930
🏛️ Government
⚕️ Healthcare Insurance
🌍 Social Impact
Government • Healthcare Insurance • Social Impact
U. S. Department of Veterans Affairs is a federal government institution dedicated to caring for United States veterans. The organization provides a variety of services, including health care, disability compensation, education benefits, and vocational rehabilitation. It also offers assistance with home loans, life insurance, and burial services, aiming to support veterans and their families in many aspects of their lives. The VA addresses issues such as mental health support, homelessness, and minority representation within the veteran community. Through its comprehensive programs, the VA seeks to improve the quality of life for veterans and service members.
Senior Data Engineer / Analytics Engineer – AWS
Job not on LinkedIn
🕒 April 20
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U.S. Department of Veterans Affairs
10,000+ employees
Founded 1930
🏛️ Government
⚕️ Healthcare Insurance
🌍 Social Impact
Government • Healthcare Insurance • Social Impact
U. S. Department of Veterans Affairs is a federal government institution dedicated to caring for United States veterans. The organization provides a variety of services, including health care, disability compensation, education benefits, and vocational rehabilitation. It also offers assistance with home loans, life insurance, and burial services, aiming to support veterans and their families in many aspects of their lives. The VA addresses issues such as mental health support, homelessness, and minority representation within the veteran community. Through its comprehensive programs, the VA seeks to improve the quality of life for veterans and service members.
📋 Description
• Design, build, and maintain robust ETL/ELT pipelines across AWS-native data environments • Own Airflow orchestration — scheduling, dependencies, retries, alerting, and operational support • Develop analytics-ready data models in dbt, using modular, warehouse-first transformation patterns • Work confidently across S3 (raw, staged, curated) and Redshift Serverless for storage and warehousing • Contribute to the roadmap and potential migration toward Snowflake as a future warehouse • Write clean, maintainable Python for pipeline logic, scripting, and lightweight engineering tasks • Embed data quality, testing, and observability into every pipeline — not as an afterthought • Apply sound version control, code review, and CI/CD practices to data workloads • Engage directly with client stakeholders: gather requirements, present solutions, and advise on trade-offs • Partner with analysts, product teams, and other engineers in a distributed, remote-first setup • Contribute to architectural reviews, retrospectives, and continuous improvement of platform practices
🎯 Requirements
• 5+ years in data engineering, analytics engineering, or closely related roles • Strong hands-on AWS data platform experience — S3-centred flows, cloud-native data workflows, warehouse-driven delivery • Apache Airflow — proven experience designing, maintaining, and troubleshooting production pipelines • dbt — solid analytics engineering patterns, modular models, testing, and documentation • Warehouse experience — Redshift preferred; Snowflake highly desirable; comparable warehouse backgrounds considered if adaptable • Python — confident scripting for pipelines, transformations, and automation • Strong understanding of data modelling (dimensional, wide tables, incremental strategies) • Excellent written and verbal communication — able to explain technical work credibly to non-technical audiences • Self-directed delivery in a fully remote, client-facing environment
🏖️ Benefits
• Continuous learning culture • Internal knowledge sharing • Sponsored technical events
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