Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Governance Lead

NHBC
Milton Keynes
4 days ago
Create job alert
Overview

We’re looking for a Data Governance Lead to define and lead NHBC’s approach to data governance, ensuring our data is well owned, well defined, and consistently understood across the organisation. You’ll play a key role in building confidence in how data is used, helping colleagues treat it as a trusted product that drives smarter decisions.

Reporting to the Senior Data Enablement Manager, you’ll own NHBC’s data governance framework and guide its practical adoption across business and technology teams. This is a great opportunity for someone who enjoys turning strategy into action, bringing structure, clarity, and accountability to how data is managed and used.

What You’ll Do
  • Lead and continuously improve NHBC’s data governance framework, policies, and standards
  • Define and embed data ownership, stewardship, and accountability across teams
  • Act as the go-to expert for data governance, offering guidance, challenge, and support
  • Maintain NHBC’s business glossary and metadata standards
  • Embed governance practices into change initiatives and day to day operations
  • Coordinate governance forums, stewardship groups, and data reviews
  • Support data elements of audits, regulatory reviews, and risk assessments
  • Promote a data as a product approach that ensures trusted, valuable data assets
  • Collaborate closely with colleagues in data quality, literacy, engineering, and architecture
  • Track and report progress on governance adoption and maturity
What You’ll Bring
  • Senior experience in data governance, data management, or information policy roles
  • Proven track record in defining and embedding governance frameworks or operating models
  • Experience working across business and technical teams to drive data ownership and accountability
  • Strong stakeholder management, communication, and coaching skills
  • Confidence leading structured discussions on roles, responsibilities, and data usage
  • Deep understanding of data governance principles, metadata, and stewardship
  • Knowledge of frameworks such as DAMA or DCAM
  • Understanding of how governance, quality, and literacy connect to create trusted data
  • Excellent communication skills, both written and verbal
What We Offer

Our benefits package includes:

  • 27 days annual leave + bank holidays
  • holiday purchase scheme
  • enhanced pension scheme (up to 10.5%)
  • life assurance
  • subsidised private medical insurance
  • employee discounts platform
  • two days volunteer leave
  • enhanced maternity, paternity, adoption leave and pay for all new parents
  • many more!

Salary: £55,000 - £60,053 plus 10% performance bonus

Working location: Milton Keynes, Hybrid

Employment type: Full time, Permanent

We are committed to fostering an inclusive culture where everyone feels empowered to bring their authentic selves to work. We support flexible working and encourage our colleagues to find a balance that suits them. We remain open to conversations about flexible arrangements and equal opportunity employment.


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Governance Lead

Data Governance Lead

Data Governance Lead

Data Governance Lead

Data Governance Lead

Data Governance Lead Analyst

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.