Head of Data Engineering
Role details
Job location
Tech stack
Job description
We have a great new role for a Head of Data Engineering to join our Data Monetisation team. This is a brand new role responsible for leading the data engineering function and building scalable, privacy-safe data products that drive commercial value from complex data assets.
This is a hands-on senior role, owning engineering strategy, architecture and delivery within a commercially focused data product environment. This role is 60% leadership/strategy and 40% hands on working with Python, SQL, GCP, AI solutions.
As Head of Data Engineering, you will be responsible for leading and mentoring a team of 4 in the creation and maintenance of our strategic data products. This programme operates within data monetisation and AI application, developing high value customer signals and data segments derived from a complex, multi source data ecosystem.
You will define the architectural strategy for our extensible and reusable data platform and act as the team's delivery lead, managing the agile workflow and roadmap priorities in coordination with senior management and key stakeholders.
Working primarily in the Google Cloud ecosystem, you will make high level decisions on data platforms, governance, data privacy and lead the evaluation and adoption of new technologies to drive innovation across the team., * Define and own the technical strategy and architecture for the data product platform, ensuring systems are extensible, reusable and scalable.
- Lead the team's agile process, facilitating stand ups, managing the backlog and setting roadmap priorities with senior stakeholders.
- Mentor a team of Product Data Engineers, providing technical guidance, support and fostering professional growth.
- Drive high standards for data quality, output accuracy, platform SLAs, data privacy and governance.
- Evaluate, prototype and recommend new technologies and tooling to continuously improve team efficiency and product capabilities.
- Maintain an understanding of data consumers and paying customers to ensure product development is aligned with high value business outcomes.
- Ensure data lineage, accessibility, privacy and security are correctly implemented throughout the data lifecycle
Who we are
Who we are
The UK's fastest broadband network. The nation's best-loved mobile brand. And, one of the UK's biggest companies too. We put our customers first, making life simpler, smoother, and more joyful. With big ambitions and a brilliant team, we're building a more connected future for everyone.
Our ways of working
We're a flexible-first organisation, because we know people do their best work when they have choice and clarity. To support meaningful collaboration, we ask everyone to spend at least eight days each month connecting in person.
That doesn't just mean time in the office, it could be team meetings, offsites, volunteering days, cross-functional projects, or away days - anywhere meaningful collaboration happens. What matters is making those moments purposeful, so when we come together, it really counts.
Accessible, inclusive and equitable for all
Requirements
- Technical leadership of remote engineering teams
- Strong Python and SQL skills; writes clean, maintainable, production-grade code
- Architecture ownership for complex, scalable data and ML/AI solutions
- End-to-end data platform design (ingestion, modelling, analytics)
- Google Cloud (or equivalent) experience incl. BigQuery, Analytics Hub, Cloud Functions, dbt
- Commercial mindset with evidence of data product adoption, cost and delivery awareness
- Clear communicator across technical/non-technical audiences, up to C-suite
- Experience building external-facing SaaS or data products with partners
- Working within data contracts, privacy and regulatory constraints
- Effective delivery in ambiguous, fast-paced environments (Agile, Jira, Confluence)
- Coaching engineers with strong hands-on Python and SQL capability
The other stuff we are looking for
- Built new products from scratch (greenfield over legacy)
- Worked with sensitive data in regulated industries (e.g. telco)
- Experience with data cleanrooms (Google, Snowflake or equivalent)