SteerBridge
Principal Data Architect & Technical Product Owner
$170K–$190K
Vienna, VA +1 · Hybrid · Principal · Full-time · Posted Oct 30, 2026
- Location
- Vienna, VA
Washington, DC - Experience
- At least six years of professional data architecture experience and at least two years of demonstrated hands-on technical Product Owner experience; the experience may be concurrent.
- Education
- Bachelor’s degree or higher in Computer Science, Systems Engineering, Data Science, or a related field.
- Visa sponsorship
- U.S. citizenship required.
About the job
Own enterprise data architecture and serve as Technical Product Owner for the Modern Disability Claims data pipeline, guiding architecture, backlog decisions, and Scrum delivery.
What you'll do
- Define target-state data architecture and direct cloud data platform and pipeline design.
- Prioritize the technical backlog, make product decisions, and guide sprint delivery for data engineering teams.
- Mentor teams, improve Agile delivery practices, and communicate architecture, risks, and roadmaps to stakeholders.
What they ask for
- U.S. citizenship and ability to obtain a Public Trust clearance; active Secret or Top Secret clearance also satisfies this requirement.
- Bachelor’s degree or higher in Computer Science, Systems Engineering, Data Science, or a related field.
- At least six years of professional data architecture experience and at least two years of hands-on technical Product Owner experience; may be concurrent.
- Enterprise-scale cloud data architecture ownership, hands-on backlog prioritization and sprint guidance, Agile/Scrum team improvement experience, and proficiency with SQL and Python.
Nice to have
- Experience with federal claims, healthcare, clinical, or other regulated data, including HIPAA and federal requirements.
- Experience with data governance, AI/ML-ready platforms, dimensional modeling, Data Vault, multi-cloud, or cloud platform DevOps practices.
Pay
USD 170,000–190,000 (per-year-salary) base salary
Tools
AWS, Azure, GCP, SQL, Python, Pandas, PySpark, Git
AI focus
Enable analytics and AI/ML use cases through reliable, governed, reusable data infrastructure; support AI/ML-ready data platforms, analytics, feature pipelines, and data science teams.
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