About THG

We are THG, a global ecommerce group on a mission to be the global online leader in beauty and sports nutrition.

Our portfolio of leading retailers and brands such as LOOKFANTASTIC, Myprotein, ESPA, Perricone MD, and Cult Beauty form our two core businesses: THG Beauty and THG Nutrition.

From Manchester to New York, we’re powered by a team of over 2500 people who work together, lead by example, and think BIG.

With us, you’ll go further, faster. What are you waiting for?

Location: Icon 1, WA15 0AF

About Central Functions

Central Functions is formed of the teams and people that serve the entire business. These people are integral to the smooth running of the business; ensuring everyone is paid on time, that materials are sourced and arrive promptly, that we meet our legal obligations and that our health, safety, and security is safeguarded.

Why be the Data Engineering Lead at THG?

THG is building the data engineering capability that will underpin everything from daily trading analytics to AI-driven personalisation. As Engineering Lead, you will own the technical vision and delivery for how THG structures, stores and distributes its data across three core domains: Customer, Commercial and Operations.

This is a hands-on technical leadership role. You will be managing and mentoring a team of six engineers (three Senior, three mid-level, each domain-aligned), but you are also expected to be technically deep — setting architecture standards, making key design decisions, and being the person the team turns to when problems are hard.

Your primary mission is to move THG from a fragmented, siloed data landscape towards consistent, joined-up domain datasets that can be trusted and used at scale. We have customer data in multiple places, commercial data that isn't consistently structured, and operational data that isn't easy to consume. You will build the engineering foundation that changes that — working to a shared architecture that ensures Customer, Commercial and Operations datasets have consistent standards, shared attributes where appropriate, and can ultimately be joined into a single, reliable view of the business.

You will work closely with Ingenuity, our technology partner, who manage the foundational platform and first-layer pipelines. Your job is to take what Ingenuity provides and shape it into the structured, high-quality domain datasets that analytics and data science teams can confidently build on. You will also be a key partner to the Data Governance Lead, implementing the standards they define within your engineering practice.

What you'll do:

Technical Leadership & Architecture

Own the data engineering architecture for THG — defining how data is ingested, transformed, stored and made available across Customer, Commercial and Operations domains
Design consistent standards and patterns across all three domains — ensuring shared attributes are handled uniformly and that data can be reliably joined across domains
Lead the evolution of our BigQuery/GCP platform — driving migrations, modernising legacy pipelines, and building for scalability
Make key architectural decisions and be accountable for the technical quality of everything the engineering team produces
Develop and enforce engineering standards across the team — version control, testing frameworks, error handling, documentation and code review practices

Domain Dataset Development

Lead the build-out of structured, reliable domain datasets — moving from disparate, siloed data sources towards consolidated Customer, Commercial and Operations data platforms
Work towards the foundations of a single source of truth — defining how data from different source systems is reconciled, deduplicated and mastered within each domain
Ensure domain datasets are structured for downstream consumption — analytics teams, data science models, BI tooling and AI/agent use cases should all be able to reliably consume what engineering produces

AI-Enabled Engineering

Champion the use of AI in data engineering — this is a small team with a large remit, and we expect AI-assisted development to be embedded in how we work
Apply AI tools to accelerate pipeline development, automated testing, anomaly detection and data quality monitoring
Stay current with AI developments in the data engineering space and bring new approaches into the team's practice

Ingenuity Relationship

Work closely with the Ingenuity engineering team — understanding what they provide at the platform layer and building effectively on top of it
Define clear requirements and interface standards for how Ingenuity data feeds into PLC domain datasets
Identify and escalate where Ingen platform behaviour affects data quality or availability within PLC domains

People & Team

Manage, coach and develop a team of six domain-aligned engineers — three Senior Data Engineers and three Data Engineers
Run a structured review and development process for each engineer, building their technical capability and career progression
Foster a culture of engineering excellence, collaboration and continuous improvement

What skills and experience do I need for this role?

Essential

Hands-on, expert-level experience with BigQuery and GCP — this is non-negotiable; you must have built and operated production data pipelines on this stack
Strong Python skills —