Data Governance Manager

DWP Digital
Blackpool
1 month ago
Applications closed

Related Jobs

View all jobs

Data Governance Manager

Data Quality and Governance Manager

Data Quality Manager

Data Governance & Enablement Manager

Data Quality Manager

Data Analyst/Manager


Job Title Data Governance Manager

Pay of £44,447, plus 28.97% employer pension contributions, hybrid working, flexible hours, and great work life balance.

DWP. Digital with Purpose.

Are you passionate about shaping how data is used to improve outcomes for millions of people? Do you have ideas on how to improve data governance processes?

We're looking for talented Data Governance Managers to join our Chief Data Office (CDO).

If you're excited by the challenge of transforming complex data landscapes and want the opportunity to influence the future of data within DWP, this could be the role for you.

As the largest government department, data underpins everything we do informing policy, guiding operational decisions and enabling us to deliver vital services that support society every day.

You'll be joining us at a pivotal moment. With DWP's five year Data Strategy launched in 2023 and a new Data Hub and Spoke model rolling out, you'll help shape a more connected and mature data ecosystem across the organisation. Working closely with the CDO and DWP Digital.

You'll also benefit from extensive development opportunities, including professional qualifications, on the job learning, and the chance to build highly transferable data skills valued across industry.

What skills, knowledge and experience will you need?

  • <...

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.

Products

Where to Advertise Data Science Jobs in the UK (2026 Guide)

Advertising data science jobs in the UK requires a different approach to most technical hiring. Data science spans a broad and often misunderstood spectrum — from statistical modelling and experimental design through to machine learning engineering, product analytics and AI research. The strongest candidates identify firmly with specific subdisciplines and are frustrated by adverts that conflate data scientist with data analyst, business intelligence developer or machine learning engineer. General job boards produce high application volumes for data roles but consistently fail to match specialist data science profiles with the right opportunities. This guide, published by DataScienceJobs.co.uk, covers where to advertise data science roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

Jobs

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

Careers

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.