Data Quality & Governance Engineer

🔒 Confidential Employer
Posted 7 May 2026
LOCATION
London
TYPE
Full-time
LEVEL
Mid-Senior level
CATEGORY
Data & Analytics
This employer holds a UK Home Office sponsor license — sponsorship for this specific role is at the employer’s discretion

SKILLS

Python SQL dbt AWS Data Governance Data Quality CI/CD Metadata Management

FULL DESCRIPTION

Data Quality & Governance Engineer

[Employer hidden — sign up to reveal] is hiring a hands-on Data Quality & Governance Engineer to build and run the governance that underpins our Data & AI function. You will work closely with the Head of Data & AI, engineers, AI/ML team, risk, and technology partners. Hybrid role – London office 3 days a week.

What You Will Do

  • Data Quality and Observability by Design: Implement automated data quality checks, alerts, and observability for critical datasets, data products, and AI features (Python, SQL, dbt). Work with source system teams to fix data at source. Embed controls in pipelines (schema, referential integrity, freshness, PII, data contracts). Define and monitor data SLIs/SLOs. Integrate quality signals into monitoring and incident tooling.
  • Build and Run Governance Operations: Design and operate the Data & AI governance spine. Implement enterprise data catalogue, glossary, end-to-end lineage, ownership/stewardship metadata. Ensure governance tooling reflects actual data flows.
  • Enable Safe, Governed AI and Analytics: Make core data assets AI-ready through provenance, documentation, and quality. Integrate governance with AI services and model lifecycle tooling. Partner with Data Scientists and ML Engineers.
  • Support Stewardship, Risk and Compliance: Work with Data Owners and Stewards to identify Critical Data Elements. Implement classification, retention, access control. Provide lineage, quality coverage, and control effectiveness views.
  • Technical guidance: Provide code review for governance and quality patterns. Contribute to shared practices for governance as code, CI/CD, testing. Evaluate governance and observability tooling.

What We Are Looking For

Essential

  • Significant experience in data-focused engineering role with emphasis on data quality, governance, or observability.
  • Experience with financial data or regulated industries.
  • Strong hands-on Python and SQL for checks, automation, and integrations.
  • Proven experience implementing automated data quality rules and monitoring (dbt tests, custom checks, observability tools).
  • Practical understanding of data governance (catalogue, lineage, ownership, CDEs, access control) and operationalisation.
  • Experience with cloud-native data platforms, ideally AWS (Redshift, S3, Glue, Lambda, IAM).
  • Familiarity with modern data modelling (dbt, dimensional modelling, star/snowflake schemas).
  • Experience with CI/CD and infrastructure as code (GitHub Actions, CodeBuild, Terraform).

Desirable

  • Experience with data governance platforms (Collibra, Atlan, Alation, OpenMetadata).
  • Experience with data observability tooling (Monte Carlo, Coralogix).
  • Exposure to ML/AI pipelines, model registries, feature stores (MLflow, Evidently).
  • Experience defining data products with SLAs and contracts.

Benefits (UK-based roles)

  • Competitive salary & learning opportunities.
  • Open and inclusive culture.
  • Hybrid working.
  • Vitality Health Plan (private health insurance, travel insurance, gym discounts).
  • Health cash Plan (Medicash Level 3).
  • 6% employer pension contribution.
  • Life assurance – 4x salary.
  • Income protection insurance – 75%.
  • 28 days holiday + 3 additional days, plus ability to sell up to 5 days.
  • Swap public/bank holidays for alternative days.
  • Enhanced family friendly policies.
  • Retail discounts and team socials.

This role is hybrid – 3 days per week in the London office. [Employer hidden — sign up to reveal] is a UK-licensed bank, wholly owned by [Employer hidden — sign up to reveal]. Apply via the Greenhouse form on this page.

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