Data Governance Consultant (Data Quality)

Day Rate: Up to £600 per day (Inside IR35) Location: London (Hybrid — 2 days per week on-site) Duration: 6 months initial (with scope for extension) Start Date: Immediate — within 10 working days Az-Tec Talent is supporting a leading consultancy on a large-scale Master Data Management (MDM) and Data Governance transformation programme for a global retail client. We're looking for a Data Governance Consultant with a strong Data Quality specialism to lead the detailed design of the enterprise Data Quality capability that underpins the wider programme.

About the Role This is a detailed-design role at the heart of the programme's governance workstream. The high-level capability designs are complete; this engagement is about translating the Data Quality capability into a detailed, implementation-ready design — the rules, profiling, monitoring, remediation, and issue-management processes that downstream teams will later implement. You'll work as part of a small team of data governance specialists covering three capabilities — Data Quality, MDM Performance, and Ownership & Stewardship. The team designs each capability in detail in turn, starting with Data Quality, so while you'll lead on DQ, you'll also contribute to the detailed design of the other two as the team works through them. A note on the environment: this moves at pace — each capability is designed in detail (not implemented) on tight timelines — and the master data attributes, models, and target architecture are still being defined, with DQ tooling not yet selected. You'll be comfortable in that ambiguity: shaping the capability, surfacing key design decisions and dependencies early, and producing clear, structured documentation the wider team can work from.

Key Responsibilities Lead the detailed design of the enterprise Data Quality capability, building on the completed high-level design and producing clear, implementation-ready artefacts and processes Work as part of a small team of governance specialists — leading on Data Quality and contributing to the detailed design of MDM Performance and Ownership & Stewardship as the team works through each capability in turn Define DQ rules and the rule library, and determine how and where rules are applied across domains Design DQ profiling, measurement, and monitoring approaches, working from profiling outputs as they become available Design end-to-end DQ issue management — clear accountability, resolution SLAs (not just notification), and escalation paths to drive issues through to closure Design DQ remediation processes and define how they will be adopted into BAU Define meaningful DQ KPIs and metrics tailored to the client's specific challenges and priorities — not generic best-practice templates Identify and clearly call out key dependencies (e.g. tooling and execution-engine placement, domain onboarding timelines, Ownership & Stewardship readiness) Maintain a clean boundary between Data Quality (rules and their application) and the governance roles, structures, and stewardship models owned by the Ownership & Stewardship capability Produce clear, reader-focused design documentation — explaining the capability as a narrative and journey rather than as lists — that the wider team can collaborate around Engage senior stakeholders across business and technology to build understanding and alignment Programme Scope Enterprise MDM foundation programme spanning multiple domains (e.g. Customer, Product, Finance) Delivered across three data governance capabilities — Data Quality, MDM Performance, and Ownership & Stewardship — designed in detail by a small, collaborative team Current phase is detailed design (not implementation): producing the artefacts, rules, and processes to be implemented in a later phase Primary focus for this role: the Data Quality capability — rules, profiling, monitoring, remediation, issue management, and DQ KPIs Required Experience Strong experience as a Data Quality / Data Governance Consultant on enterprise programmes Proven track record designing enterprise Data Quality frameworks and producing detailed, implementation-ready design artefacts Hands-on experience defining DQ rules, profiling, monitoring, and remediation Experience designing DQ issue management — resolution SLAs, escalation routes, and end-to-end accountability Experience defining DQ KPIs and metrics aligned to real business priorities Comfortable working at pace, producing detailed designs to tight timelines as part of a small, collaborative delivery team Comfortable operating in a pre-tooling, evolving-architecture environment, surfacing dependencies and design decisions early Experience working at the interface between Data Quality and ownership/stewardship functions, with the judgement to keep workstream boundaries clean Strong storytelling and documentation skills — able to explain a capability as a clear narrative, with the reader front of mind Confident engaging and influencing senior stakeholders MDM programme exposure and a working understanding of metadata management Retail industry experience highly beneficial