Data Governance Consultant

We are looking to recruit an SC Cleared Data Governance Consultant for a leading technology consultancy.

You will work with clients to establish and improve practical data governance frameworks, covering areas such as data quality, metadata, lineage, stewardship, policy and standards. The role will also involve supporting the responsible governance and assurance of AI solutions, although the core requirement is strong data governance experience.

This is a client-facing consulting role, working across multidisciplinary data, architecture, engineering and security teams.

Due to the nature of the work valid SC Clearance is required.

What you’ll be doing

• Delivering data governance frameworks, policies, standards and operating models.
• Defining stewardship models, governance roles, RACI structures and decision-making forums.
• Establishing data quality rules, measures, scorecards and remediation processes.
• Supporting metadata management, business glossaries, data catalogues and lineage.
• Helping clients classify and protect sensitive data and improve auditability.
• Running stakeholder workshops to understand requirements and translate them into practical governance solutions.
• Producing governance documentation, operating procedures, risk assessments and assurance reports.
• Supporting AI governance and assurance, including data provenance, bias, privacy, model evaluation and ongoing monitoring.
• Working alongside data architects, engineers, security specialists and other consultants.
• Supporting and coaching more junior members of the team.

Skills: SC Clearance, Data Governance, Data Quality, Metadata Management, Data Lineage, Data Stewardship, You should have strong practical experience delivering data governance or data management initiatives, ideally within a consulting, public sector or regulated environment.

Experience should include several of the following:

• Data governance frameworks and operating models.
• Data quality management and remediation.
• Data stewardship and ownership models.
• Metadata management and data cataloguing.
• Data lineage.
• Business glossaries.
• Data classification and sensitivity.
• Data privacy, retention and access controls.
• Governance policies, standards and procedures.
• Stakeholder workshops and client-facing consulting.

Some understanding of AI governance or AI assurance would be beneficial, particularly around training data quality, provenance, bias, model evaluation, monitoring and risk management. Deep hands-on machine learning experience is not required.

Exposure to tools such as Microsoft Purview, Collibra, Alation, Databricks, Microsoft Fabric, Azure ML or Power BI governance would also be useful.

Experience within Defence, Central Government, hydrography, sonar, geospatial/mapping or offshore industries such as oil & gas would be particularly relevant.