Data Governance Manager

Leeds
6 days ago
Create job alert

My client is based in the Yorkshire area are currently looking to recruit for an experienced Data Governance Manager to join their Data & AI Consulting team. They are a specialist within their domain, that are at the forefront of engineering practices. They are currently going through a period of growth and are looking for an experienced Governance Professional to join their team. They only recruit the "best" talent and have a diverse workforce.

Your role will include:

  1. Governance Strategy
    Develop and execute a data governance and quality framework aligned with business goals and global standards.

  2. Data Architecture & Pipelines
    Partner with data engineering teams to build structured, reliable, and trusted datasets.

    Embed governance and quality controls into pipelines and manage seamless data migrations.

  3. Master Data Management (MDM)
    Implement MDM processes to standardize core domains (customer, vendor, product, location).

  4. Data Profiling & Quality
    Lead data profiling efforts and design quality rules to improve data health and trustworthiness.

  5. Collaboration with Engineers
    Work closely with engineering teams to integrate validation and quality checks into data pipelines.

  6. Data Protection & Access Governance
    Implement classification models and role-based access to secure sensitive and critical data.

  7. Data Lineage Documentation
    Maintain end-to-end data lineage for transparency across data sources, transformations, and usage.

  8. Critical Data Element (CDE) Management
    Identify, prioritize, and govern Critical Data Elements essential for operations and reporting.

  9. Data Migration Support
    Oversee governance during migrations to protect data quality, integrity, and security.

  10. Governance Tools Enablement
    Deploy and manage governance platforms (e.g., Microsoft Purview, OneLake) and ensure integration with the data ecosystem.

    My client is providing access to;

    Hybrid 3 days in office,
    29 Holidays,
    Flexible Working,
    Private Health Care,
    And More...

    For this role they are looking for a candidate that has experience in…

    Azure Data Platform,
    Strong knowledge of Snowflake, with the ability to work closely with Data Engineers to ensure data quality checks are embedded, Exposure to governance tools such as: Purview, OneLake etc, CDMP, or DCAM certified
    Strong experience designing and managing data pipelines in modern cloud environments, Familiarity with data governance tools such as Collibra, Alation, Atlan.

    This role is an urgent requirement, there are limited interview slots left, if interested send an up to date CV to Shoaib Khan - (url removed) or call (phone number removed) for a catch up in complete confidence.

    TRG's Data Teams offer more opportunities across the UK than any other recruiter We're the proud sponsor and supporter of SQLBits, AWS RE:Invent, Power Platform World Tour, the London Power BI User Group, Newcastle Power BI User Group and Newcastle Data Platform and Cloud User Group

Related Jobs

View all jobs

Data Governance Manager

Research and Data Governance Manager

Data Governance Team Lead / Stratford-Upon-Avon / Tech4Good / Data Quality / Data Enrichment

Information Asset Register Lead

Data Warehouse Architect (Basé à London)

BI/MI Manager

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

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

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.

Data Science Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Data science has become one of the most sought‑after fields in technology, leveraging mathematics, statistics, machine learning, and programming to derive valuable insights from data. Organisations across every sector—finance, healthcare, retail, government—rely on data scientists to build predictive models, understand patterns, and shape strategy with data‑driven decisions. If you’re gearing up for a data science interview, expect a well‑rounded evaluation. Beyond statistics and algorithms, many roles also require data wrangling, visualisation, software engineering, and communication skills. Interviewers want to see if you can slice and dice messy datasets, design experiments, and scale ML models to production. In this guide, we’ll explore 30 real coding & system‑design questions commonly posed in data science interviews. You’ll find challenges ranging from algorithmic coding and statistical puzzle‑solving to the architectural side of building data science platforms in real‑world settings. By practising with these questions, you’ll gain the confidence and clarity needed to stand out among competitive candidates. And if you’re actively seeking data science opportunities in the UK, be sure to visit www.datascience-jobs.co.uk. It’s a comprehensive hub featuring junior, mid‑level, and senior data science vacancies—spanning start‑ups to FTSE 100 companies. Let’s dive into what you need to know.

Negotiating Your Data Science Job Offer: Equity, Bonuses & Perks Explained

Data science has rapidly evolved from a niche specialty to a cornerstone of strategic decision-making in virtually every industry—from finance and healthcare to retail, entertainment, and AI research. As a mid‑senior data scientist, you’re not just running predictive models or generating dashboards; you’re shaping business strategy, product innovation, and customer experiences. This level of influence is why employers are increasingly offering compensation packages that go beyond a baseline salary. Yet, many professionals still tend to focus almost exclusively on base pay when negotiating a new role. This can be a costly oversight. Companies vying for data science talent—especially in the UK, where demand often outstrips supply—routinely offer equity, bonuses, flexible work options, and professional development funds in addition to salary. Recognising these opportunities and effectively negotiating them can have a substantial impact on your total earnings and long-term career satisfaction. This guide explores every facet of negotiating a data science job offer—from understanding equity structures and bonus schemes to weighing crucial perks like remote work and ongoing skill development. By the end, you’ll be well-equipped to secure a holistic package aligned with your market value, your life goals, and the tremendous impact you bring to any organisation.