Lead Data Engineer

Simmer is one of the UK’s fastest-growing consumer brands, built on a simple idea: healthy food should taste extraordinary. Founded by brothers Simmy and Jhai with £10 of ingredients, we’ve grown into a profitable, bootstrapped £100M+ ARR business and were ranked #5 in The Sunday Times 100 fastest-growing companies.

But we still think we’re early.

Our ambition is to become the defining brand in healthy eating.

We’re fully founder-led, with no private equity or corporate layers. Decisions happen quickly, ownership is real and the people who join us have the opportunity to materially shape how Simmer operates as we scale. Behind every subscription, order, refund, acquisition decision and operational movement is data the business needs to trust.

We’ve built the foundations quickly and now we need to make them excellent.

The opportunity

We’re looking for a Lead Data Engineer to take technical ownership of the engineering behind Simmer’s data platform. There is already a real platform in place. Our data is centralised in Microsoft Fabric, with ingestion into a lakehouse, dbt transformation and a warehouse layer feeding reporting and applications across the business. Today that includes roughly 15 staging models, 45 intermediate models and 90 marts across revenue, acquisition, customers, LTV, costs, menu and operations.

The challenge is that Simmer has grown faster than some of the engineering discipline around it.

Pipelines can still fail too quietly. Models have multiplied as new business questions have appeared. Some concepts are represented in more than one place. And parts of the platform were built for the scale we had at the time rather than where we’re going next.

Your job is to change that. Take a platform built quickly for a fast-growing business and make it robust enough for the next stage of scale.

This is a hands‑on role. You’ll build, debug, restructure and ship yourself, while also setting the technical standard for how the platform evolves.

Why the data is interesting

Simmer isn’t a typical ecommerce business.

A customer can subscribe, skip, pause, change plan, cancel and later reactivate.

Transactions, refunds and customer states don’t always move at the same point in that journey.

So apparently simple questions can become genuinely interesting modelling problems.

What is an active customer?

When has someone actually churned?

Which revenue belongs to which period?

How should customer value be represented over time?

You won’t be expected to arrive as the commercial owner of every answer.

But you will need to understand the business logic behind those questions, work closely with Finance and commercial teams and build data foundations that allow the business to answer them consistently.

What you’ll own

Your focus will be on three things:

• Make the pipelines reliable. Own and improve ingestion from our source systems, strengthen monitoring and observability, and make sure failures are surfaced before the business finds them.
• Build better models. Lead the evolution of our dbt layer, simplify duplicated and ad‑hoc models, and create a structure that can support the next question rather than another one‑off answer.
• Make the data trustworthy. Work closely with Commercial and Finance to understand the business logic behind key metrics and make sure agreed definitions are implemented cleanly and consistently in the data layer.

You’ll also set modelling standards, improve testing, CI and orchestration, handle late‑arriving data and restatements properly, and make governed data easier for our BI application, tools and AI agents to consume.

Not every problem needs a platform rebuild. Part of the job is knowing what deserves proper engineering, what needs simplifying and when the business simply needs a reliable answer quickly.

The kind of person we’re looking for

• First and foremost, you’re an excellent hands‑on Senior/Lead Data Engineer.
• You’re already operating with, or are ready for, broader technical ownership.
• You’ve probably worked in a scaling environment where the data platform mattered, but wasn’t perfect.
• You know how to inherit something real, understand it quickly and make it materially better without needing to rebuild everything from scratch.
• You want broad ownership, but you still want to be close to the work.

You’ll likely have strong experience across:

• SQL
• dbt
• Python
• orchestration
• Git and CI
• testing, reliability and observability

You might have worked with Fabric, Synapse, Snowflake, BigQuery, Databricks or Redshift.

You don’t need to know our exact stack.

We care more about what you’ve built, the judgement you bring and whether you can make good technical decisions in an environment that moves quickly.

Experience with subscription, ecommerce or D2C data is useful, but not essential.

And you don’t need to have previously been the commercial owner of metrics.

You do need to be curious about what the numbers actually mean, comfortable working directly with non‑technical stakeholders and able to turn ambiguous business questions into robust, repeatable data solutions.

Why this role?

Most Lead Data Engineers have to choose between scale and ownership.

At a large technology company, you may work at scale but own one small part of the platform. At an early startup, you may get huge ownership but spend years waiting for the complexity to arrive. This role sits unusually between the two.

Simmer already has meaningful scale, real technical complexity and a platform the business depends on every day, but the data organisation is still small enough that your decisions will materially shape how it works.

You’re not being asked to invent a data function from nothing. You’re inheriting a real platform inside a £100M+ business that has outgrown some of its early engineering choices.

The foundations exist.

The problem is clear.

The impact is visible.

Take technical ownership of a real data platform inside one of the UK’s fastest-growing consumer businesses and make it genuinely excellent.