Head of Data Platform & Monetisation

This isn't a data engineering job where you maintain someone else's mess. You're building the platform.

Our client sits on one of the most valuable datasets in the UK. Millions of customers. Rich behavioural signals. A complex, multi-source data ecosystem that most companies could only dream of.

The problem? That value doesn't unlock itself. Right now, they're building the infrastructure to turn raw data into high-value customer signals and commercial data products, and they need the right person to lead it.

As Head of Data Engineering, you'll own the architectural strategy, lead a team of four Product Data Engineers, and sit at the intersection of technical delivery and business outcomes. You'll report into the Director of Data Monetisation and work with stakeholders from engineers up to C-suite.

• Define the architecture - Own the technical strategy for a data product platform that's extensible, reusable, and built to last — not patched together as requirements evolve.
• Lead the team - Manage the agile process, run standups, own the backlog and roadmap, and mentor four Product Data Engineers to grow technically and professionally.
• Drive quality and governance - Set high standards across accuracy, platform SLAs, privacy, and data lineage — and make sure they hold throughout the entire data lifecycle.
• Push innovation - Evaluate and prototype new technologies and tooling. You'll have room to shape how the team works, not just what it builds.
• Deliver commercial value - Stay close to data consumers and paying customers to keep product development tied to outcomes that actually matter to the business.

• Proven technical leadership: You've led a team of engineers remotely, challenged architectural decisions, and driven the right practices for the team.
• Full-stack data experience at scale: Ingestion, ML/AI modelling, analytics. You've designed complex end-to-end solutions, not just one layer of the stack.
• Google Cloud hands-on experience: BigQuery, Analytics Hub (BQ Sharing), Cloud Functions and DBT Cloud specifically. Comparable cloud experience considered for strong candidates.
• Commercial mindset: You can demonstrate data product adoption and articulate the time and cost value of what you've built.
• External data product experience: You've built SaaS or data products for external partners, including data contracts, integrations, and privacy constraints.
• Agile fluency: Jira and Confluence are part of your daily life. You handle ambiguity well and thrive in fast-moving environments.
• Python and SQL coaching ability: You can develop engineers, not just write clean code yourself.

• Nice to have, but not required: Experience building new products from scratch rather than inheriting legacy systems.
• Sensitive datasets in regulated industries, especially telco.
• Data cleanrooms - Google, Snowflake or equivalent.

• Real architectural scope: Own the direction of a strategic data platform at one of the UK's largest telcos — not just execute someone else's vision.
• Interesting data at scale: UK-scale telco data. Complex signals. The kind of dataset that takes years to build.
• Commercial backing: Data monetisation is a growth priority. This team has real business support behind it.
• Strong benefits: 40% bonus long-term incentive plan after 3 years service, Bupa healthcare from day one, income protection, life assurance, birthday day off, and the option to buy or sell up to 5 days holiday.

Most data engineering roles ask you to maintain what's already there. This one asks you to build what comes next. If that's the kind of problem you want to spend your time on, apply now to find out more!