Principal Data Architect & Technical Product Owner

SteerBridge•Washington, DC

10d•$170,000 - $190,000•Hybrid

About The Position

SteerBridge is seeking a senior technical leader to own enterprise data architecture and serve as the Technical Product Owner for the Modern Disability Claims (MDC) data pipeline. The role combines hands-on architectural direction with independent product prioritization, backlog decisions, sprint delivery accountability, and mentorship for Scrum teams. The successful candidate will translate mission and program priorities into scalable designs, clear engineering work, and measurable delivery outcomes, while communicating effectively with senior SteerBridge and VA stakeholders. The position is based in a hybrid arrangement in Vienna, Virginia, with an expected on-site presence of at least three days per week, subject to supervisor direction. The salary range is $170,000–$190,000 per year. A final offer depends on relevant experience, skills, education, certifications, work location, and position responsibilities; contract requirements, wage determinations, and federal contract labor categories may also inform the offer.

Requirements

U.S. citizenship and ability to obtain a Public Trust clearance; an 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 demonstrated, hands-on technical Product Owner experience, including independent responsibility for backlog prioritization, product decisions, and Scrum delivery. These experiences may be concurrent if both capabilities are clearly demonstrated.
Demonstrated ownership of enterprise-scale data architecture in a cloud environment, including data modeling, platform design, and data integration.
Actual experience independently prioritizing a technical product backlog, making backlog decisions, and guiding sprint execution for an engineering or data team; a formal Product Owner job title is not required.
Demonstrated experience improving Agile/Scrum team maturity through hands-on product ownership, coaching, mentorship, and effective backlog management, sprint planning, and delivery practices.
Proficiency with SQL and Python, and practical experience with relevant data engineering tools and workflows such as Pandas, PySpark, and Git.
Experience with enterprise data warehouses or lakes such as Databricks, Redshift, BigQuery, or Snowflake, or comparable platforms.
Ability to brief senior executives and government stakeholders, explain architectural tradeoffs, and mentor technical teams.
Ability to work in a hybrid arrangement based in Vienna, VA, with an expected on-site presence of at least three days per week, subject to supervisor direction.

Nice To Haves

Experience with federal claims, healthcare, clinical, or other regulated and sensitive data environments, including HIPAA and federal data requirements.
Experience establishing enterprise data modeling standards, master data management, metadata catalogs, lineage, and data governance.
Familiarity with dimensional modeling, Data Vault, OLTP/OLAP architecture, and hybrid or multi-cloud design.
Experience supporting AI/ML-ready data platforms, analytics, feature pipelines, and data science teams.
Infrastructure as code, CI/CD, DevOps, and cost/performance governance for cloud data platforms.

Responsibilities

Own the target-state architecture for claims, clinical, and healthcare data, including conceptual, logical, and physical models, integration patterns, and cloud data platforms.
Independently prioritize and maintain the technical product backlog; define epics, user stories, acceptance criteria, dependencies, and delivery priorities in partnership with mission stakeholders.
Own product decisions and sprint delivery outcomes for data engineering Scrum teams; guide sprint planning, refinement, reviews, and continuous improvement in coordination with team facilitators.
Lead and mentor MDC Scrum teams, improving Agile delivery practices, backlog refinement, sprint planning, execution discipline, and delivery predictability; coach engineers, junior architects, and Scrum team members in technical delivery, product ownership practices, and architecture standards.
Design scalable batch and real-time ETL/ELT pipelines, schema evolution, data quality controls, lineage, observability, and governance.
Direct cloud platform architecture and technology decisions across AWS, Azure, or GCP and enterprise warehouse/lake technologies.
Apply appropriate access controls, sensitive-data safeguards, and federal and healthcare data handling requirements.
Enable analytics and AI/ML use cases through reliable, governed, reusable data infrastructure.
Lead architecture reviews, resolve cross-system tradeoffs, and communicate roadmaps, risks, priorities, and technical decisions to executive and government stakeholders.