Data Analytics Engineer
AcquiredBirmingham, England, United Kingdom
Added 18 Jul · still live
Not disclosed
Salary
Not disclosed by employer
£54,900
Going rate
Skilled Worker going rate
This role likely qualifies for a Skilled Worker visa
Our predicted code SOC 2133 (67% match) is an eligible occupation, with a going rate of £54,900, and Acquired is a licensed sponsor. That is our reading of the published rules. Whether they issue a Certificate of Sponsorship is still their call.
About the role
Technology
Sometimes the chance comes up to be part of something really special, at Acquired you’ll be collaborating with teams and people who challenge you, support you, and inspire you to be extraordinary.
We’re Acquired
Recurring Payments. Redefined.
Acquired helps businesses win and retain customers. We process payments intelligently and optimise every aspect of the recurring payment lifecycle.
We combine this capability with exceptional sector expertise and a highly personal, tailored service focused on long-term partnerships with our customers.
How we work matters as much as what we build. We’re hugely ambitious and passionate about recurring payments. As a team, we pride ourselves on being relentlessly focused on results.
If that's how you operate, you could be a great fit for Acquired.
Your Mission
Acquired's commercial, product, finance, and payments teams increasingly run on data. The Data & Analytics team turns warehouse data into the metrics, models, and analysis those teams use to make decisions.
This is a Data Analytics Engineering role — modelling, semantic layer, and stakeholder-facing analysis — not data infrastructure. Pipeline orchestration, ingestion, and platform work is owned elsewhere on the team.
We're open on level. The role is a fit for:
The day-to-day mix sits across:
- Midlands
- Fully Remote
Sometimes the chance comes up to be part of something really special, at Acquired you’ll be collaborating with teams and people who challenge you, support you, and inspire you to be extraordinary.
We’re Acquired
Recurring Payments. Redefined.
Acquired helps businesses win and retain customers. We process payments intelligently and optimise every aspect of the recurring payment lifecycle.
We combine this capability with exceptional sector expertise and a highly personal, tailored service focused on long-term partnerships with our customers.
How we work matters as much as what we build. We’re hugely ambitious and passionate about recurring payments. As a team, we pride ourselves on being relentlessly focused on results.
If that's how you operate, you could be a great fit for Acquired.
Your Mission
Acquired's commercial, product, finance, and payments teams increasingly run on data. The Data & Analytics team turns warehouse data into the metrics, models, and analysis those teams use to make decisions.
This is a Data Analytics Engineering role — modelling, semantic layer, and stakeholder-facing analysis — not data infrastructure. Pipeline orchestration, ingestion, and platform work is owned elsewhere on the team.
We're open on level. The role is a fit for:
- An early-career engineer or analyst keen to learn modern analytics engineering on the job.
- A strong data analyst ready to step into modelling, dbt, and end-to-end ownership.
- An established analytics engineer who wants a broad, high-agency remit across a payments business.
The day-to-day mix sits across:
- Modelling — building and maintaining the warehouse models (facts, dimensions, marts) that downstream analysis depends on.
We use Claude Code heavily across the team — for dbt model authoring, ticket implementation, documentation maintenance, code review, and analytical exploration. You'd be expected to be comfortable working alongside it from day one, or get comfortable quickly. We have a written operating model for how engineers and agents work together; we'll share it with you during the process.
What That Looks Like In Practice
- Humans stay accountable. The agent does work; you own the result. Human attention is spread across the workflow — intent, approach, in-flight, sign-off — rather than concentrated at PR review.
- We extend the tooling. Custom skills tailored to our stack, MCP integrations across the tools we use day-to-day, slash commands and hooks for repetitive workflows. Curating these is engineering work — you'll use what's there, refine what isn't working, and propose new things.
- Evidence-first investigation — we expect both humans and AI agents to cite file/line, query output, or commit history before making claims. "Trust but verify" applies to everything an assistant produces.
What You'll Bring
We do not expect you to have prior experience with every tool in our stack. SQL is our only hard-and-fast technical requirement. For the rest, we're looking for strong analytical fundamentals and a high capacity and eagerness to learn.
Must-haves
If you have experience with some of these, that's great. If not, you should be excited to learn them:
Must-haves
- SQL — fluent or rapidly improving. Window functions, CTEs, performance-sensitive query design. We use BigQuery.
- Analytical thinking — ability to break down ambiguous problems, interpret data, and translate findings into decisions.
- Self-direction — comfortable owning work and asking for help when stuck. Your manager is an active individual contributor, so expect low control and high agency.
- Communication & stakeholder posture — comfortable proactively setting up meetings, interviewing stakeholders, and writing things down. Visiting Nottingham/London to build relationships in person.
- Eagerness to learn — excited about picking up new tools (dbt, the Semantic Layer, Dagster, Data Studio, BigQuery ML) on the job.
If you have experience with some of these, that's great. If not, you should be excited to learn them:
- Dimensional modelling — facts, dimensions, grain, how to extend a model without breaking downstream consumers.
- dbt — staging/intermediate/mart layers, tests, snapshots, macros, incremental models.
- Semantic layers (dbt Semantic Layer ideally; Cube.dev or LookML transferable).
- Data Studio or another BI tool.
- Payments or fintech domain (cards, acquiring, IC++ pricing, routing) — domain training is fine if you bring strong fundamentals.
- Working alongside AI coding assistants (Claude Code, Cursor, Copilot) — comfortable delegating, reviewing, and steering AI-generated work.
- A two-person Data & Analytics team inside Acquired's wider Engineering function.
- A modern warehouse stack: BigQuery, dbt (Core/Semantic Layer, moving toward Fusion), Dataflow (Beam) for extracts, Data Studio for dashboards, Dagster (deploying mid-year) for orchestration.
Midlands
High Performance and Values driven culture
We have high expectations and work hard to deliver exceptional results.
We value open and honest communication and are committed to listening to our people. Your ideas make us better.
You’ll be collaborating with high performing teams and people who challenge you, support you, and will inspire you to be extraordinary!
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Technology
- Midlands
- Fully Remote
Sometimes the chance comes up to be part of something really special, at Acquired you’ll be collaborating with teams and people who challenge you, support you, and inspire you to be extraordinary.
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This description is the source posting as it read when we added it. We are not affiliated with Acquired, so check their own site for the current details.
Where this offer sits in the market
SOC 2133 · UK · ONS ASHE 2025 · ~163k in sampleP25 £46kP75 £82k
£36kmedian £60kgoing rate £55k£100k
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Does this job guarantee visa sponsorship?
Not necessarily. Acquired holds a sponsor licence, but sponsorship for a specific hire is always the employer's decision. Be upfront in your application that you'll require it.
What salary is needed for this role to be eligible?
The offer must clear both the general threshold and the SOC 2133 going rate of £54,900. New-entrant and shortage discounts can lower it.