Data Governance Lead – Programme Advance General Business - Smiths Group - Birmingham

Smiths Group plc.
Birmingham
3 weeks ago
Create job alert

Location:

United Kingdom

Ref:

REF3823J

Job Function:

General Business

Company Description

Smiths Group designs, manufactures and delivers smarter engineering solutions for mission‑critical applications, solving some of the world's toughest problems for our customers, our communities and our world. For over 170 years, Smiths Group has been pioneering progress by improving the world through smarter engineering.

We serve millions of people every year, to help create a safer, more efficient and better‑connected world, across four major global markets: Energy, General Industry, Security & Defence, and Aerospace. Listed on the London Stock Exchange, Smiths employs 14,600 colleagues in over 50+ countries.

This pioneering spirit continues to drive us today, underpinned by our powerful culture. Improving our world is what we do, how we think, and how we will continue to use our passion for technology and engineering to tackle our customers biggest challenges today and in the future. We're looking for people with curious minds. Who want responsibility and relish a challenge. Whether you're an experienced professional or just starting out, our global scale and focus on growth means we have some great career opportunities for you. There's never been a better time to join Smiths.

  • The Data Governance Lead will be pivotal to the success of Programme Advance, the HCM and Payroll transformation initiative—by ensuring that the foundation of all transformation activities is built on high-quality, trusted, and compliant data.
  • This role will drive the development and implementation of policies, standards, and processes that support seamless data integration, master data management, and regulatory compliance.
  • Through proactive stewardship and continuous improvement, the Data Governance Lead will help mitigate risks, address data‑related pain points, and foster a culture of data‑driven innovation.
  • You will lead the establishment, management, and continuous improvement of the company’s data governance framework. Support senior management in developing and executing the organization’s strategic plan for data quality, compliance, and stewardship. Oversee the development and enforcement of data policies, standards, and processes to ensure the integrity, security, and effective use of data across Smiths Group and its divisions.
Responsibilities
  • Develop, implement, and maintain data governance policies, standards, and procedures to ensure high-quality, trusted data across the organization.
  • Establish and govern master/reference data, data quality management, data cataloguing, data lineage, and traceability as foundational pillars for all business units.
  • Collaborate with business and technical stakeholders to define data ownership, stewardship, and accountability models.
  • Lead initiatives to improve data quality, resolve data issues, and drive adoption of data governance best practices.
  • Oversee compliance with legal, regulatory (GDPR), and company requirements for data privacy, security, and usage.
  • Facilitate the creation and maintenance of business glossaries, data dictionaries, and metadata management tools.
  • Provide guidance and training to data stewards, business users, and technical teams on data governance principles and practices.
  • Monitor and report on data governance metrics, including data quality KPIs, policy adherence, and remediation progress.
  • Support the integration of data governance into project delivery, change management, and business‑as‑usual (BAU) activities.
  • Act as a subject matter expert and escalation point for complex data governance queries and issues.
  • Foster a culture of data stewardship and continuous improvement across the organization.
  • Develop and design approval processes using workflows for master data.
  • Define data quality metrics and drive continuous system and data improvement.
Qualifications
  • Educated to degree level or equivalent.
  • Strong understanding of data governance frameworks (e.g., DAMA‑DMBOK), data management principles, and industry best practices.
  • Strong experience with data quality management, data cataloguing, metadata management, and data lineage tools.
  • Familiarity with data privacy regulations (e.g., GDPR) and compliance requirements.
  • Proficiency in data management platforms (e.g., Azure Data Lake, Databricks) and BI tools (e.g., PowerBI).
  • Excellent analytical, problem‑solving, and organizational skills.
  • Experience working with both onshore and offshore teams.
  • Strong communication and stakeholder engagement skills, with the ability to interact at all levels of the organization.
  • Experience in developing and delivering training and documentation for data governance initiatives.
  • Passion for data, technology, and continuous improvement.
Additional InformationDiversity & Inclusion:

We believe that different perspectives and backgrounds are what make a company flourish. All qualified applicants will receive equal consideration for employment regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, economic status, disability, age, or any other legally protected characteristics. We are proud to be an inclusive company with values grounded in equality and ethics, where we celebrate, support, and embrace diversity.

At no time during the hiring process will Smiths Group, nor any of our recruitment partners ever request payment to enable participation – including, but not limited to, interviews or testing. Avoid fraudulent requests by applying jobs directly through our career’s website (Careers - Smiths Group plc ).


#J-18808-Ljbffr

Related Jobs

View all jobs

Lead Data Scientist

Data Governance Lead - Programme Advance

Data Governance Lead

Executive Director: BHF Data Science Centre

Smart Data Architect - Health Construction- London / Birmingham

BI & Data Transformation Manager

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.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.

Data Science Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Thinking about switching into data science in your 30s, 40s or 50s? You’re far from alone. Across the UK, businesses are investing in data science talent to turn data into insight, support better decisions and unlock competitive advantage. But with all the hype about machine learning, Python, AI and data unicorns, it can be hard to separate real opportunities from noise. This article gives you a practical, UK-focused reality check on data science careers for mid-life career switchers — what roles really exist, what skills employers really hire for, how long retraining typically takes, what UK recruiters actually look for and how to craft a compelling career pivot story. Whether you come from finance, marketing, operations, research, project management or another field entirely, there are meaningful pathways into data science — and age itself is not the barrier many people fear.