Data Governance & AI Consultant

CALIO Consulting Group; West of England; On-site; GBP 70,000 - 90,000; Full time

Job summary

CALIO Consulting Group is recruiting a Senior Data & AI Governance Consultant to help clients build robust governance foundations and responsible AI.

You will work under broad direction to deliver engagements, advise on best practices, and produce artefacts such as policies, standards, operating models, and evaluation frameworks that measurably improve data quality, model reliability, risk posture and compliance.

Qualifications

• Proven experience delivering data governance programs.

Responsibilities

• Deliver data governance workstreams: policies & standards, roles & RACI, stewardship models, data issue management, and data quality measurement & remediation.

Skills

Data governance

Policy & standards

RACI & governance

Data quality

Metadata & catalogues

Privacy & protection

AI assurance

Training data

Model selection

Testing & evaluation

In-life governance

SFIA Level 4

Stakeholder facilitation

English proficiency

SC clearance

Tools

Microsoft Purview

Azure ML

Databricks/MLflow

Azure Fabric

Power BI governance

Collibra

Alation

Job description

Location: UK (Hybrid) with travel to client sites 2 days p/w across Bristol, Portsmouth and Taunton

Contract: Permanent, full-time

Security clearance: Minimum SC (active & lapsed would be ok)

Notice - ideally 1 month notice

Briefing notes:

• Defence experience desirable

• Sonar work and underwater mapping

• Hydrographic office experience would be interesting

• Oil & gas also another transferable industry due to work in seas

Why this role matters

Our customer partners with UK Central Government and Defence to deliver trusted, value-driven data and AI outcomes. We're recruiting a Senior Data & AI Governance Consultant to help clients build robust data governance foundations and adopt responsible, well-assured AI. You'll work under broad direction to deliver engagements, advise on good practice, and create practical artefacts-policies, standards, operating models, and evaluation frameworks-that measurably improve data quality, model reliability, risk posture, and compliance.

What you'll do

Delivery & client engagement (SFIA L4 - Enable)

• Deliver data governance workstreams: policies & standards, roles & RACI, stewardship models, data issue management, and data quality measurement & remediation.

• Design and implement metadata & cataloguing (business glossary, lineage capture, classification & sensitivity labels) using client-standard platforms.

• Contribute to AI assurance across the lifecycle:

• Training data readiness (provenance, quality, representativeness, bias checks, privacy & IP considerations, synthetic data controls).

• Model selection support (fit-for-purpose criteria, interpretability needs, security constraints, compute/cost trade-offs).

• Test & evaluation (appropriate metrics and acceptance thresholds; robustness, fairness, privacy, and safety testing; secure red-teaming where applicable).

• Operational governance (monitoring KPIs, drift detection, incident response, change control, and regular re-evaluation & re-training with realistic datasets).

• Author clear artefacts: governance frameworks, operating procedures, evaluation plans, model cards/datasheets, risk assessments, and assurance reports.

• Run workshops and interviews with stakeholders, capturing requirements and converting them into actionable designs and backlogs.

• Support benefits tracking (e.g., DQ uplift, lineage coverage, model performance stability, incident reduction).

Methods, tools & assurance

• Apply and tailor customer playbooks for data governance and AI assurance (policy templates, DQ standards, risk & control libraries, evaluation checklists).

• Configure/enable client tools (e.g., Microsoft Purview for governance/lineage/labels; Azure ML / Databricks / Fabric for MLOps, model registry, monitoring; Power BI governance).

• Contribute to assurance reviews and quality gates; maintain well-structured evidence for audits and approvals.

Consulting & collaboration

• Work in multi-disciplinary teams with data architects, platform engineers, and security colleagues; manage day-to-day stakeholder communications.

• Contribute to proposals and estimates; create slideware and demos for pre-sales and discovery.

• Coach junior consultants; share knowledge through internal communities of practice.

What you'll bring (Essential)

• Proven experience in data governance delivery, including:

• Policy & standards, stewardship models, RACI, decision forums.

• Data quality (dimensions, rules, scorecards, monitoring, remediation).

• Metadata & catalogue adoption (business glossary, lineage, classification & sensitivity).

• Privacy & protection in data handling (e.g., DPIAs, retention, access control, auditability).

• Practical understanding of AI assurance, covering:

• Training data preparation and validation (provenance, quality, representativeness, bias mitigation).

• Model selection considerations (interpretability, performance, risk, security constraints).

• Testing & evaluation (appropriate metrics, benchmarking, robustness/fairness/privacy tests, safe red-team exercises).

• In-life governance (monitoring, drift detection, risk logging, periodic re-evaluation and re-training with realistic data, change approvals).

• Strong consulting fundamentals: structured problem-solving, facilitation, documentation, and stakeholder communication.

• Ability to work under general direction, plan own work, and enable others-aligned to SFIA Level 4 expectations.

• Excellent written/spoken English.

• Minimum SC clearance (active) and willingness to travel to UK client sites.

Desirable

• Experience in UK Central Government, Defence, or other regulated/public sector environments.

• Familiarity with established frameworks/standards (e.g., DAMA-DMBOK for data; NIST AI RMF 1.0, ISO/IEC 23894 AI risk management, ISO/IEC 27001, UK GDPR/DPA 2018).

• Hands-on exposure to one or more platforms: Microsoft Purview, Azure ML, Databricks/MLflow, Azure Fabric, Power BI governance; plus experience with data catalogues (e.g., Collibra, Alation) is a bonus.

• Exposure to MLOps processes (model registry, approval workflows, monitoring, incidents & rollbacks) and risk/control libraries (e.g., bias, robustness, security, IP, privacy).

• Awareness of secure development and deployment constraints (e.g., air-gapped networks, protective monitoring, model and data escrow).