OverviewSteampunk is seeking a
Data Governance SME to design, implement, and help operationalize data governance practices - including metadata management, data cataloging, and stewardship workflows - for a large federal client's data environment, ensuring data assets are discoverable, trustworthy, and well-governed. The role also supports assessment of data quality, governance maturity, and AI-related data risk.
Contributions- Assess current-state data assets, governance practices, and interoperability constraints, and deliver a Data Management Framework
- Implement and maintain data catalogs, metadata repositories, and business glossaries to improve data discoverability
- Support definition and rollout of data stewardship and ownership models, including issue management and lifecycle processes
- Conduct exploratory data analysis to uncover trends and identify data quality issues informing remediation priorities
- Operate a data-quality remediation tracking process with monthly reporting, supporting identification and remediation of data quality issues
- Facilitate alignment between technical teams and business stakeholders on data definitions, quality expectations, and usage standards
- Support streamlined, user-centered data access-request workflows and access controls, in alignment with data classification principles
- Partner with the Data Architect to ensure the underlying data environment supports accurate, complete, and consistent data, including metadata capture and lineage tracking
- Deliver quarterly data maturity assessments with specific improvement recommendations, including catalog coverage and adoption metrics
- Communicate data quality and governance maturity findings clearly to technical and executive stakeholders
- Support technical analysis behind the AI Compliance and Risk Management Plan's bias and training-data-quality sections, including data origin, quality, and known limitations
- Contribute data lineage and data card documentation supporting the AI Compliance and Risk Management Plan's data origin and quality assessments
- Maintain well-organized, audit-ready documentation of data assessments, findings, and remediation activity
Qualifications- Ability to obtain and maintain a U.S. government security clearance
- Bachelor's degree, preferably in Information Systems, Data Management, Data Science, Business Analytics, Computer Science, or a related field, and 10+ years of total experience
- 6+ years of data governance, data management, or data science experience
- Demonstrated experience assessing data quality and building data governance frameworks, including stewardship operating models
- Understanding of metadata types (business, technical, operational), data lineage, and schema management concepts
- Familiarity with data privacy, security, and access control concepts, including experience supporting data access-request workflows
- Proficiency with data analysis and query tools (e.g., SQL, Excel) to assess data quality and structure
- Working knowledge of machine learning/AI training data concepts sufficient to assess data quality, origin, and bias considerations (not hands-on model development)
- Strong written and verbal communication and facilitation skills, with the ability to translate technical data findings for both technical and executive audiences
- Local to Baltimore, MD metro area and willing to go on client site at least 2 days a week
Preferred:- Experience assessing bias or quality issues in training data for AI/ML use cases
- Federal data governance experience
- Master's degree in a related field
- Experience with data cataloging/governance platforms (e.g., Collibra, Alation, Atlan, Informatica, or cloud-native catalog tools)
- Familiarity with cloud data platforms
- DAMA CDMP (Associate or Practitioner), Collibra Ranger, or Alation Steward certification
