Senior Data Engineer

Data moves fast, and the businesses that win are the ones whose data can keep up with their ambition. That is the problem this role exists to solve, and it is a genuinely interesting one.

As our Senior Data Engineer at Protein Works, you will be the person who owns the pipelines, the warehouse, and the data infrastructure that the rest of the business quietly depends on every single day. Not for the sake of a tidy architecture diagram, and not to build something impressive that nobody queries. For leverage: making decision-making across marketing, trading, operations and finance faster, more trustworthy, and more commercially effective by building infrastructure the business actually relies on.

This role sits inside a growing and highly capable Business Intelligence team, at the heart of Protein Works' AI transition. That means you will be laying clean, well-governed foundations that let AI workflows, agents, and analytical tooling deliver real value, not inheriting someone else's half-finished setup. You will work across our Google Cloud data stack, connect APIs and pipelines into coherent systems, and take ownership of the full journey from initial brief through to a pipeline running reliably in production. If you are the kind of engineer who takes pride in clean pipelines, fast queries, and infrastructure that just works, this is a role worth reading on about.

About Protein Works

Founded in 2012 on a clear conviction: the sports nutrition industry had become complacent, and there was a better way to do it. Over a decade later, we are a £50m business with five consecutive years of double-digit growth, a brand new £10m campus in Liverpool, and ambitions that go well beyond where we are today.

We are growing, investing and hiring with purpose. If you want to join a business with the energy of a challenger and the foundations of a market leader, this is the right moment to do it.

What you will be doing

Owning BI infrastructure end-to-end, from initial brief and requirement gathering through to data pipeline development across APIs, ETL, ELT and SQL

Working alongside Data Analyst colleagues to help them generate impactful business insights and analysis

Taking day-to-day responsibility for the quality, security and performance of our Data Lake and Warehouse

Building and maintaining robust CI/CD processes for data pipelines using tools such as Cloud Build and GitHub, raising the standard of how code is tested, deployed and version-controlled

Proactively monitoring pipeline health, optimising performance, and managing infrastructure costs to ensure efficient scaling

Applying strong data modelling, semantic consistency and metadata discipline so data is discoverable and usable by both humans and AI tools

Partnering with function-specific AI engineers and analysts to understand their data needs and unblock them quickly

Using AI tooling to accelerate your own engineering, from code generation to pipeline documentation to data quality checks

Championing knowledge sharing and best practice across the team and wider business

What success looks like

Demonstrable data engineering experience with a data warehouse platform, with pipelines and infrastructure you can point to

Extremely strong SQL skills, non-negotiable

Significant hands-on experience integrating APIs into real, production data flows

Experience with the Google Cloud Platform data stack, including BigQuery, Cloud Functions, Cloud Storage, Pub/Sub, IAM Management, and Data Studio

Strong working knowledge of Python for pipeline development, automation, and tooling integration

Hands-on experience with Cloud Build and GitHub for version control and CI/CD

A working understanding of how to keep data AI-ready: strong modelling, semantic consistency, and metadata discipline that both humans and AI tools can rely on

Comfortable working across the full data landscape that a growing DTC business touches: marketing, trading, operations and finance

Able to take a messy brief and turn it into a structured, working pipeline without needing it handed to you step by step

A high personal standard for detail and communication, because the data you ship becomes the truth other teams build decisions on

A degree is not required for this role. What matters is what you have built, what you can show, and how you think about problems.

Nice to have: hands-on experience with dbt, Dataform or equivalent transformation and orchestration frameworks; familiarity with Terraform or equivalent infrastructure-as-code tooling; comfort with vector databases, embeddings, or semantic search; and working knowledge of Google's marketing stack, including Google Analytics, Google Tag Manager, Google Ads and Google Search Console.

You are the kind of person who designs for systems running reliably without you, not for you firefighting them. You ask whether a pipeline will hold up at scale before you ship it. You are commercially grounded enough to connect every piece of infrastructure back to speed, cost, or trust in the numbers, and you are honest enough to flag a problem rather than let bad data quietly spread. You are energised by pace, not exhausted by it, and you are comfortable in an environment where the team is figuring things out together. Twelve months from now, success looks like this: the data platform is faster and more trustworthy, AI workflows across the business are running on foundations you built, and you are already halfway through the next problem.

What you will get

Exclusive staff discounts

Private healthcare

Birthday day off

Pension scheme

Unique bonus scheme

Cycle to work scheme

Access to retail discounts

Staff socials and events

State of the art PW Campus

WFH on Fridays

Refreshments on-site

REF-229 659