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

Apply Now

Data Governance Positions - Data Analytics & Management

Venn Group
London
5 months ago
Applications closed

Related Jobs

View all jobs

Data Quality Manager

Azure Data Engineer

Data Scientist – CLV & Next Best Action United Kingdom, London

Staff Data Scientist - CLV & Next Best Action

Staff Data Scientist – CLV & Next Best Action London (England) Sony Interactive Entertainment D[...]

Staff Data Scientist – CLV & Next Best Action United Kingdom, London

Multiple Data Governance Positions – Interim

We are currently recruiting on behalf of a major banking client for a number of Data Governance Analysts at various corporate levels to play key roles in an ongoing Data Transformation Programme.

The ideal candidate will have knowledge of Data Governance, BCBS239, ECB onboarding and Operational Risk management practices.

This is a strategic opportunity for an experienced professional to contribute to the development and execution of the EMEA Data Strategy within a growing Data Office.

The successful candidate will work closely with stakeholders across the organisation, providing critical support to enhance data governance practices—particularly within the Risk and Finance domains. As some data governance principles are still maturing within the organisation, the role will also require an individual with strong influencing skills and the ability to educate stakeholders at all levels on the importance of data governance and management.

Key Responsibilities:

  • Lead the implementation of data governance activities across Risk and Finance domains in alignment with BCBS239 regulatory standards.
  • Take ownership of data definition, lineage, and governance for priority use cases, ensuring end-to-end oversight.
  • Monitor changes in business data requirements, coordinating change and release management processes across data domains.
  • Collaborate with cross-functional stakeholders to develop and promote adoption of EMEA-wide data standards and governance frameworks.
  • Investigate data quality issues and support the development of remediation strategies to address root causes.
  • Champion a culture of data accountability, driving improvements in architecture, management, and quality practices.
  • Contribute to the broader transformation efforts led by the EMEA Data Office, which span cultural, behavioural, procedural, and systems-based change.

Key Requirements:

  • Deep knowledge of data governance, data quality, and data analysis techniques, particularly within the context of Risk and Finance.
  • Strong understanding of BCBS239 regulations and their application within Tier 1 or Tier 2 banking environments.
  • Proven experience engaging and influencing senior stakeholders, including executive and board-level communication.
  • Expertise in complex data structures, with a strong grasp of Risk and Finance data calculations and domain knowledge.
  • Familiarity with enterprise-level data management principles, including logical, physical, and business data modelling.
  • Analytical thinker with a track record of delivering effective, practical solutions.
  • Proficient in Microsoft Excel, Visio, and PowerPoint, with experience in business process modelling.
  • Collaborative team player with the capability to work independently when required.
  • Professional presence, excellent communication, and strong presentation skills.
  • Prior exposure to Collibra or similar data governance tools is highly advantageous.

Desirable Skills:

  • Experience supporting ECB onboarding initiatives.
  • Familiarity with data visualisation and collaboration tools such as Power BI, Tableau, and SharePoint.
  • Exposure to technical tools including SQL, Python, R, and data engineering frameworks.
  • Understanding of data-related regulatory compliance and emerging trends within the data management space.

#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.

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.