Head of Data Governance & Strategy

Franklin Fitch
City of London
1 month ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Head of Business Intelligence & Data Analytics

Head of BI Business Intelligence and Data

Senior Data Architect

Data Quality Manager

Senor / Lead Data Engineer

Location: City of London (3 days per week in office)


Reports to: Chief Data Officer


Team Size: 6 (Data Architects and Data Compliance specialists)


We’re partnered with a FTSE 250 fintech powerhouse seeking an experienced Head of Data Governance and Strategy to lead their global data governance framework and strategic data initiatives.


This critical leadership role will establish and maintain robust data governance standards, policies, and compliance frameworks across their international operations spanning the EU, USA, and Australia.


The Role

Reporting directly to the Chief Data Officer, you’ll lead a team of 6 professionals (data architects and data compliance specialists), ensuring data assets are managed, protected, and leveraged effectively while maintaining regulatory compliance in the financial services sector.


Key Responsibilities

  • Define, implement, and maintain the enterprise data governance framework, policies, and standards across global operations
  • Establish data quality standards, metadata management practices, and master data management strategies
  • Lead data stewardship programmes and ensure accountability for data assets across business units
  • Drive data governance maturity through continuous improvement initiatives
  • Ensure compliance with FCA, GDPR, SEC, FINRA, and ASIC requirements
  • Oversee data privacy, protection, ethics, regulatory reporting, and audits
  • Develop and execute data strategy aligned with business objectives
  • Define data architecture principles and champion data literacy organization-wide
  • Partner with Legal, Compliance, Risk, IT, and data engineering teams (London, Eastern Europe, India)
  • Embed governance in technical platforms (GCP, AWS, Oracle)

Essential Candidate Experience and Skills

  • 10+ years in data governance, management, or related fields in large, complex organizations
  • Proven track record implementing enterprise-level data governance frameworks
  • Strong knowledge of financial services regulations (FCA, GDPR, SEC, ASIC)
  • Experience managing data compliance/privacy in multi-jurisdictional environments
  • Demonstrated leadership of cross-functional teams
  • Excellent stakeholder management and influencing skills
  • Understanding of data architecture principles (hands-on not required)
  • Experience with cloud data platforms (GCP, AWS) and modern data architectures
  • CDMP/DGSP/CIPP certifications
  • Financial services/fintech background

If you think this role aligns, let’s talk. Please apply directly here or reach me below to arrange an initial call.


#J-18808-Ljbffr

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.

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.

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.

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.