At a Glance
- Tasks: Lead a dynamic data team, driving innovation and modernisation in data engineering.
- Company: Join Nominet, a leading domain name registry making a positive societal impact.
- Benefits: Enjoy a 34-hour work week, generous leave, private healthcare, and a pension scheme.
- Other info: Embrace a culture of accountability, continuous improvement, and diversity.
- Why this job: Make a real difference in data management while developing your leadership skills.
- Qualifications: Experience in managing teams and a strong background in data engineering required.
The predicted salary is between 72000 - 88000 £ per year.
Location: Hybrid, with a minimum of 20% in the Oxford office per month
About Us: We’re Nominet – a world-leading domain name registry operating at the heart of the UK internet. While we're best known for running .UK domains, our DNS expertise also underpins critical internet infrastructure that government services, including the NHS, rely on. As a public benefit company, our work has a positive impact on society. We’ve donated millions to projects that use technology to improve people’s lives and have committed to delivering £60m worth of support over the next three years.
The Role: Lead Nominet's Data function, bringing together data platform engineering, data analysis and database engineering as one coherent, high-performing team. This is a people leadership role first, supported by enough technical depth to set engineering standards, review designs and challenge approaches. You will lead the modernisation of our data estate towards everything-in-code, automated and rebuildable infrastructure, while treating the teams who rely on our data as customers. Success means a reliable, well-governed data platform, stronger engineering practice and a team that grows in capability and impact.
What You'll Be Doing:
- Lead, coach and develop a multidisciplinary team of approximately 11 people across data platform engineering, data analysis and database engineering, including recruitment, objectives, performance and career development.
- Build a high-performing, connected data function by creating stretch opportunities, encouraging learning across disciplines and setting a culture of accountability, psychological safety and continuous improvement.
- Own and deliver the roadmap across the Databricks platform, analytics capability and Oracle/PostgreSQL database estate, balancing strategic investment, operational demand and technical debt.
- Drive modern engineering practice across the data function, including version control, peer review, CI/CD, automated testing, infrastructure as code and eliminating manual production changes.
- Lead the transition from traditional DBA operations towards code-defined, automated and rebuildable database environments, including automated schema migrations and immutable infrastructure approaches.
- Own observability, reliability and cost management across the data estate, establishing meaningful monitoring, alerting and clear service levels for the services teams depend on.
- Make data quality, ownership, lineage, governance, security and privacy engineered properties of the platform, with clear accountability and consistent definitions for consumers.
- Build a strong product mindset around internal customers by understanding their workflows, creating feedback loops and ensuring the roadmap reflects the outcomes they need.
- Work closely with engineering, product, security, architecture, and business teams, communicating technical decisions and trade-offs clearly while managing relevant third-party and vendor relationships.
About You:
- Demonstrable experience line managing engineers or analysts, including development, performance, and recruitment; this is a genuine people leadership role.
- A strong engineering background in data: platform engineering, data engineering, database engineering, or a closely related discipline, with enough hands‑on credibility to review a design and challenge an approach.
- Practical experience with a public cloud lakehouse or modern data platform; Databricks and Spark experience is an advantage.
- Solid grounding in relational databases at scale, ideally including Oracle and/or PostgreSQL.
- Real experience of DevOps practice applied to data or databases: infrastructure as code, CI/CD, automated schema migration, configuration management.
- A track record of raising engineering standards in an existing team, not just maintaining them.
- Clear evidence of a customer or product orientation in an internal‑facing team.
- Excellent communication skills, and the judgement to know when to decide, when to delegate, and when to elevate.
Nice To Have:
- Experience leading a migration from traditional DBA operations towards an automated, code‑defined model.
- Familiarity with immutable infrastructure patterns, containerised or episodic database environments, and blue/green or expand‑contract release approaches.
- Exposure to data governance and cataloguing tooling, and to data quality frameworks.
- Experience managing a multi-disciplinary team where the disciplines do not naturally talk to each other.
- Awareness of how AI and machine learning workloads change the demands placed on a data platform.
What to expect next:
- 1st stage: Introduction call with a member of the TA team (30-45 mins)
- 2nd stage: Technical interview (60 mins)
- 3rd stage: Onsite leadership interview (60 mins)
Our Values: We Make Things Happen, We Pull Together, We Bring A Positive Mindset, We Keep It Simple. Our people make things happen, but our values are our compass as a company, guiding our day-to-day work and building our culture. They reflect that we're strongest when we're proactive and pull together, while underlining the importance of a "glass half full" mindset and aiming to keep things simple for success.
What We Offer:
- Early Finish Friday – 34-hour working week with full-time pay (finish at midday on Friday)
- 30 days annual leave plus bank holidays, with the option to buy an additional 5 days
- Bupa private healthcare + Employee Assistance Programme
- Pension scheme matched to 7%
- Electric vehicle scheme with on‑site charging points
- Rewards platform with discounts at hundreds of retailers and restaurants
- Medicash discounts on routine healthcare including optical and dental
- Annual company bonus
Diversity Statement: We're passionate about creating a workplace where every individual is valued, respected, and empowered. Somewhere we can benefit from all forms of diversity and discover the true value in our differences. If there are any adjustments we could make to the recruitment and selection process to support you, please let us know.
Security Statement: Nominet is committed to the safeguarding and welfare of the internet and expects all employees and volunteers to share this commitment by participating in the relevant security and screening processes. All roles working for Nominet will be subject to a Baseline Personnel Security Standard (BPSS) check. Some roles, due to the nature of their work, will require additional security clearance. Please note that Nominet is unable to provide visa sponsorship or relocation support for this position.
Engineering Manager - Data in Oxford employer: Nominet
Nominet is an exceptional employer that prioritises employee well-being and professional growth, offering a hybrid work model with a minimum of 20% in the Oxford office. With a commitment to a 34-hour working week, generous annual leave, and comprehensive benefits including private healthcare and a pension scheme, Nominet fosters a positive and inclusive work culture where innovation thrives. Employees are encouraged to develop their skills in a supportive environment, making it a rewarding place for those looking to make a meaningful impact in the tech industry.
StudySmarter Expert Advice🤫
We think this is how you could land Engineering Manager - Data in Oxford
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We think you need these skills to ace Engineering Manager - Data in Oxford
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Craft a Tailored Cover Letter:For a full-time role at Nominet, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Nominet. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Nominet
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Nominet!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.