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

Apply Now

Data Governance Analyst

Arthur Recruitment
London
4 weeks ago
Applications closed

Related Jobs

View all jobs

Data Governance Analyst

Data Governance Analyst

Data Governance Analyst

Data Governance Analyst

Data Governance Analyst Risk & Finance

Data Governance Analyst

Job Advertisement: Data Governance Analyst

Location: London | Type: Permanent | Sector: Insurance

*MUST HAVE INSURANCE EXPERIENCE*


Arthur has partnered with an insurance and reinsurance business that offers solutions for high-risk, high-capacity commercial and industrial enterprises, combining expertise with cutting-edge science, data, and analytics.


The Role

Were looking for a Data Governance Analyst to join our Data Team, central to sourcing, managing, and delivering trusted data via the Data Platform. Youll ensure accurate, consistent, and well-governed master and reference data, manage our data catalogue and business glossary, and support compliance and business decision-making.


Key Responsibilities

  • Master Data Management: Maintain a single, accurate view of customer data; monitor MDM processes; collaborate with data stewards; support integration into downstream systems.
  • Reference Data Management: Maintain a central reference data catalogue; validate and update reference data; align with business stakeholders.
  • Data Catalogue & Business Glossary: Document new data assets; maintain lineage, ownership, and metadata; promote catalogue adoption.
  • Data Quality & Governance: Monitor data quality; investigate issues; contribute to governance standards and continuous improvement.
  • Stakeholder Engagement: Support governance forums; provide insights on data quality; act as a first line of support for queries.


What Were Looking For

  • Experience in data governance, MDM, or RDM in complex environments.
  • Strong knowledge of data management concepts: MDM, RDM, data quality, business glossary, data lineage.
  • Practical experience with data quality monitoring and resolution.
  • Familiarity with data catalogues and metadata tools.
  • Strong SQL and analytical skills.
  • Excellent communication and stakeholder engagement.
  • Awareness of regulatory and audit requirements (e.g., Lloyds data standards).


Nice to Have:

  • Hands-on with MDM tools (Profisee, Informatica, Reltio, Microsoft MDS).
  • Experience with data catalogue platforms (Collibra, Alation, Purview).
  • Exposure to insurance/financial services data (customer, policy, claims).


Sounds good?

Apply now!!

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.

Jobs

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.

Jobs

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.

Jobs

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.

🍪 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.