At a Glance
- Tasks: Lead the establishment of a scalable enterprise data governance framework and architecture.
- Company: Join a forward-thinking organisation focused on data-driven decision-making.
- Benefits: Competitive salary, flexible working arrangements, and opportunities for professional growth.
- Other info: Dynamic role with a focus on leadership recruitment and structured handover.
- Why this job: Shape the future of enterprise data and make a significant impact on business outcomes.
- Qualifications: Proven experience in enterprise data governance and architecture in complex organisations.
The predicted salary is between 75600 - 92400 £ per year.
The business has built strong foundations for enterprise data: the function structure, a growing canonical data model, and a live platform estate. This engagement turns that design work into operating reality, establishing enterprise data as a core, permanently owned capability underpinning AI, analytics, billing, reporting and decision‑making.
Key Responsibilities
- A scalable, governed function – Establish accountable ownership of data with real authority. Make the operating model scalable enough to absorb new domains, systems and acquisitions. Leave the function able to evidence control on demand.
- Governance – Design and launch the governance framework: ownership, stewardship, lineage, quality standards and enforcing controls. Build the evidence base so the function can demonstrate control rather than assert it. Tie data quality to commercial outcomes such as billing accuracy and revenue assurance. Prove adoption in priority areas with named, bought in owners and delivered training.
- Architecture – Extend the canonical data model to remaining priority domains. Deepen mastering and target‑state definitions where gaps remain. Ensure the architecture scales through continued M&A integration. Capture the outgoing architecture lead's knowledge before departure. Provide senior direction on build‑out work, transitioning it to the incoming permanent lead. Produce a prioritised roadmap sequenced by business benefit.
- Platform FinOps – Establish the FinOps model for in‑life platform decisions, managing cost against value. For the core analytics platform, deliver this jointly with the team who own and operate it.
- Working with the Data Analytics team – Consult throughout the engagement via the Technical Design Authority's existing gates. Ensure governance and architecture support, rather than obstruct, the team as primary platform users.
- Investment case – Cost and justify the build‑out and permanent run cost, including the permanent operating model and run team, so the case funds the destination, not just the build.
- Recruitment and handover – Define and run recruitment for two permanent leadership roles, including onboarding. Structure handover so permanent leadership can operate independently by the end of the engagement. Deliver documented architecture and governance, a live evidence base, and a written statement of what is complete versus what must be maintained.
Deliverables
- A scalable, governed enterprise data function established as a permanent capability.
- A prioritised roadmap to fortify existing structures.
- A live governance framework with a demonstrable evidence base.
- Extended canonical model and operationalised definitions.
- A platform FinOps model.
- A defined working model with the Data Analytics team.
- A costed investment case.
- Two permanent leadership roles recruited and onboarded.
- A structured handover within the fixed term.
Out of Scope
- Function design, foundational architecture and platform selection, all already in place.
- Ongoing operation of the function and standing board representation, which sit with permanent leadership once appointed.
Candidate Profile
- Proven track record designing and launching enterprise data governance frameworks in a large, complex organisation.
- Strong enterprise data architecture background, ideally including canonical or mastering data models and lakehouse or medallion architectures.
- Experience building investment cases and securing funding for permanent data capabilities.
- Comfortable working through an existing design authority and governance structure.
- Experience defining and hiring into permanent leadership roles, with a clear focus on structured, time‑bound handover.
- Strong stakeholder management skills at CTO level.
- Background in regulated, billing‑sensitive or M&A‑active environments is an advantage.
Head of Governance & Architecture employer: Jefferson Frank
Join a leading UK manufacturing and supply-chain organisation that is at the forefront of digital transformation. With a strong commitment to employee development, you will have access to competitive salaries and opportunities to enhance your IT and Data management skills in a collaborative and dynamic work environment. Located in Surrey, this hybrid role offers the chance to engage with diverse stakeholders while contributing to innovative solutions that drive business success.
StudySmarter Expert Advice🤫
We think this is how you could land Head of Governance & Architecture
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We think you need these skills to ace Head of Governance & Architecture
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at Jefferson Frank, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!
Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to Jefferson Frank, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
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How to prepare for a job interview at Jefferson Frank
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at Jefferson Frank.
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
✨Highlight Your Adaptability
Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at Jefferson Frank.
✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at Jefferson Frank.
