Head of Data Platform Engineering

We’re on a mission to take the headache out of utilities by providing them all in one place. One bill for energy, broadband, mobile and insurance and a whole lot of savings! We’re aiming to double in size as we help more people to stop wasting time and money. Big ambitions, to be delivered by people like you.

We put people first. It’s all about you. We’re looking for a senior engineering leader to shape and scale our enterprise data platform on Google Cloud. You’ll guide and grow three core teams—Data Infrastructure, Data Engineering, and DataSecOps—treating our platform as a true internal product with real users, clear SLAs, and a vision you help define.

Right now, our biggest adventure is migrating our data estate onto a modern enterprise lakehouse, and you’ll be right at the heart of it. Because we believe the best leaders stay connected to the craft, this is a true player-coach role: especially in the early days, you’ll have the freedom to roll up your sleeves for hands‑on architecture, coding, and solving tough incidents alongside your teams.

Key Skills & Experience

• Proven Engineering Leadership: Significant track record leading data or software engineering functions, with deep experience managing engineering teams and managers.
• Hands‑on coding: Production‑level SQL, Python, and Terraform.
• Modern Cloud Data Stack: Deep expertise in BigQuery, Cloud Composer/Airflow, and Pub/Sub, Dataflow, or Kafka.
• Platform & DevOps: Experience with Terraform, Kubernetes, Docker, CI/CD, and observability.
• Data Architecture: Strong background in Kimball, Data Vault, and Medallion/lakehouse patterns.
• Security & FinOps: Hands‑on experience with data privacy controls (UK GDPR) and cloud cost optimisation.

We work together.

Your team and the people you will work with... Reporting to the VP of Data and AI, you’ll lead three key teams:

• Infrastructure: GCP foundations, including BigQuery, storage, orchestration, compute, networking, Infrastructure as Code, environments and developer tooling.
• Engineering: batch and streaming pipelines for ingestion, transformation and modelling, delivering trusted data products.
• DataSecOps: access control, privacy engineering, secrets management, policy-as-code and compliance automation.

You’ll partner closely with the Head of Data Science, Software Engineering, and Governance, InfoSec, and Risk teams.

We deliver progress.

What you’ll do and how you will make an impact. You’ll build and run UW’s enterprise data platform, turning core architecture into a reliable, secure, and AI‑ready platform. A key priority is driving our Data Capabilities programme, migrating our data estate to an Enterprise Lakehouse on GCP.

Core Responsibilities

• Hands‑on technical leadership: write and review SQL, Python and Terraform, lead critical designs, join major incidents and root‑cause analysis, and set engineering standards.
• Strategy and roadmap: own a multi‑year platform strategy that supports the Data & AI strategy (including real‑time and agentic AI), make build‑vs‑buy and vendor decisions, manage cloud partner relationships, and move the organisation towards data mesh and self‑service data products.
• People leadership: run a multi‑team organisation that includes managers, handle hiring and career development, and own capacity planning across permanent staff, contractors and partners.
• Reliability: set SLOs and SLAs for business‑critical data such as billing, settlement and regulatory reporting. Run CI/CD, data contracts, observability and on‑call. Scale to high‑frequency time‑series data. Own business continuity and disaster recovery.
• Security and compliance: build in IAM, RBAC/ABAC, row‑ and column‑level security, encryption, masking and tokenisation. Turn UK GDPR and sector rules into automated controls, and keep the platform audit‑ready.
• FinOps: own the platform budget (OpEx and CapEx), optimise BigQuery and storage costs, track unit costs and build investment business cases.
• AI enablement: provide feature pipelines, ML‑ready datasets, vector and embedding storage, MLOps and LLMOps (prompt and model versioning, RAG evaluation, guardrails, deployment of agentic workflows), plus model governance.
• Semantic layer and data sharing: run a central metrics layer and enable governed data sharing with external partners and regulators.
• Stakeholder leadership: present to executives, and work with Product and Engineering on data contracts and schema change management, so that breaking changes fail upstream builds before reaching production.

Additional Information

So why pick UW? We’ve got big ambitions so there’s going to be plenty of challenges. There are also a lot of benefits:

• An industry benchmarked salary. We’ll share it during your first conversation.
• Hybrid working, with 2 days in the office.
• Electric Car salary sacrifice scheme through Tusker.
• Discount on our services and you get our coveted Cashback Card for free.
• You’ll also get access to 100s of rewards and discounts through Perkbox.
• A matched contribution pension scheme and life assurance up to 4x your salary. You can also access free mortgage advice and a financial wellbeing tool.
• Family-friendly policies, designed to help you and your family thrive.
• Discounted private health insurance, access to an Employee Assistance line and a free Virtual GP. Our wellbeing app Unmind supports your mental health.
• Belonging groups that help UW shape an even more inclusive future.
• A commitment to helping you develop your career journey through learning, coaching and new experiences.

Martyna Zbyszewska will be your point of contact throughout the recruitment process. We provide equal opportunities, a diverse and inclusive work environment, and fairness for everyone. You are welcome to apply no matter your age, disability, gender, marriage or civil partnership status, pregnancy and maternity status, race, religion or belief, or sexual orientation. Please don’t be afraid to ask about what we can do to support your needs. All requests will be carefully and fairly considered. Please note, if you are successful and offered a role at UW, you will be subject to a background check. Where checks are unsatisfactory or incomplete and/or a failure to reveal information relating to convictions that you are required to identify as part of the background checks, could lead to withdrawal of an offer of employment.