Analytics Engineer​/Data Engineer

• Please be aware although we are a remote organisation we do require candidates to reside in the UK.
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Full time

Head of Analytics

Remote

Problem Shared is a practitioner-led, CQC-regulated digital mind-health provider. We assess and treat adults and young people with ADHD, autism, and specific learning differences, and we partner with NHS trusts, integrated care boards, universities, insurers, and private healthcare providers. The company was founded by clinicians who watched the NHS waitlist problem from inside an A&E and decided to do something about it.

We believe “data for good” — that good data work transforms how neurodivergent people understand themselves, how practitioners sharpen their craft, and how teams design better support. The stack we work in:
Fivetran → Databricks (Unity Catalog) → dbt → semantic layer → Power BI and R/Quarto for partner-grade reporting. Mature in some places, still being built in others. You’d help us close the gaps.

• Tool-agnostic, outcome-driven. We care more about a candidate’s mental agility and generalisable knowledge than tool-specific experience.
• Neurodiversity-welcoming. Potential over conformity. A meaningful share of our colleagues are neurodivergent. Adjustments to the process are normal, you don’t have to explain why.
• Fully remote, flexibly. Work where you do your best thinking. If you’re in London some of us meet up for coworking once a week, it’s not mandated. Psychoeducation, prescribing, educational navigation, and therapy sessions all under one roof.

You build the bridge between raw source data and the dbt layer the rest of the team builds on, working across the medallion architecture. Your craft is modelling raw, messy, real-world source data (Semble, Zendesk, CMS, finance systems) in through the medallion layers, (bronze, silver, gold) and ensuring our analysts get data they can use. Our team already includes a senior data engineer (focussed on ingestion and transformation) and a senior analytics engineer (focussed on dbt access control and restructuring the data into analyst-ready schemas), you will deputise for them both to increase capacity and reduce key-person risk.

You’ll stay close enough to our analysts that you can tell when a schema decision is going to cause pain three weeks later. The chair builds the conduit between raw data and analyst-ready data and ensures that conduit is maintainable and governable.

Half our most-used source systems land in shapes that are almost-but-not-quite usable. Bronze tables that look like APIs, prescriptions scattered across five systems, person records that don’t quite match. Your work turns those into the silver and gold foundations the rest of the data team builds on — which means every dashboard, every report, and every clinical-quality indicator downstream gets to start from solid ground.

• Model bronze source data into silver tables for analytics consumption. The headline first project is Semble, which currently lands in a heavily normalised form that’s not ready to be analysed. An old process (Power BI bolted onto complicated exports) provides an illustration of the business logic to be applied in the restructure, but you’ll have the agency to throw that old process away and build something better.
• Build upon our cross-system reconciliations for entities that span our stack — prescriptions across Semble, CMS, pharmacy and EMIS; patient identities fuzzy-joined across CMS, NHS, and insurer sources. Data needs to be reconfigured from “where is it from” to “what is it about”; so our analysts can answer business questions.
• Replace a…