Head of Data Compliance

CBSbutler Holdings Limited trading as CBSbutler

Gloucester

3 months ago

Applications closed

Related Jobs

View all jobs

Head of Business Intelligence & Data Analytics

Deputy Head of Business Intelligence

Senor / Lead Data Engineer

Data Quality Manager

Data Engineer

Senior Data Architect

Technology organisation is hiring for a permanent Head of Data Governance (Data Protection & Data Privacy) to lead all aspects of data protection, GDPR compliance, data risk and wider data governance. This is a permanent role based in Gloucester on a hybrid basis (2 days per week). You will need to undergo SC Clearance, so will need to be eligible. Salary ranges between £70K - £80K.

Responsibilities include:

* Lead and own GDPR and data protection compliance across the business, acting as the
primary point of contact.
* Advise and influence senior stakeholders, building strong relationships across
multidisciplinary teams.
* Develop, implement and maintain data protection strategies, policies, controls and
statutory records.
* Monitor regulatory developments and ensure ongoing compliance, including management
of DSARs and DPIAs.
* Lead data breach investigations and work closely with Security to ensure robust data
protection and cyber security practices.
* Review and advise on data protection aspects of contracts and oversee third-party
compliance with Supply and Commercial teams.
* Define KPIs, conduct audits, report on compliance and support engagement with
regulators, including the ICO.
* Assess data, privacy and AI-related risks, supporting the responsible use of
emerging technologies.
* Apply knowledge of cyber security principles and re...

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

Industry Insights

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

Apr 9, 2026

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.

Mar 24, 2026

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.

Feb 10, 2026

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.