Abtrace

Healthcare

DataEngineer

£85–120k ~AI est. London, England, United Kingdom FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Data Engineer at Abtrace. Skills: Data pipelines, Data warehouse, Data platform, Data infrastructure. Design data pipelines. Build data pipelines”

Industry & Context.

Healthcare
Problems you'll solve

Data-driven decision making

What They're Looking For.

Must Have

Solid experience as data engineer, Solid experience as backend engineer, Production data systems experience, SQL for data work, Python for data work, Large datasets experience, Distributed datasets experience, Design data pipelines in production, Operate data pipelines in production, Ingestion experience, Transformation experience, Orchestration experience, Cloud data platforms experience, AWS experience, Infrastructure-as-code experience, Manage data infrastructure as code, Comfort working in small team, Make architectural decisions, Clear communication

Nice to Have

AWS cloud data platforms experience, Warehouse or lakehouse experience, dbt familiarity, Airflow familiarity, Dagster familiarity, Step Functions familiarity, Healthcare industry experience, Regulated industries experience, Data governance at scale experience, Early data engineer at startup experience, Data quality background, Observability background, Platform engineering background

What You'll Do.

Design data pipelines

Maintain data pipelines

Ingest from databases

Ingest from file exports

Own data warehouse architecture

Evolve data warehouse architecture

Shape data warehouse direction

Build path for new data

Streamline adding models

Streamline changing models

Implement transformation tooling

Version-control analytics logic

Review analytics logic

Provide data controls

Provide data auditability

Establish data quality checks

Partner with analytics teams

Partner with engineering teams

Partner with product teams

Contribute to data security

Contribute to compliance

Define data platform strategy

How You'll Work.

Team & Collaboration

Analytics teams; Engineering teams; Product teams; Clinical stakeholders; Operational stakeholders

Communication Scope

Clear communication

Full Job Description

### Job Description Abtrace is solving one of the most complex, impactful problems in healthcare for a generation. The company is at an inflection point. Intelligent analysis underpins everything Abtrace does and is key to driving improvements for patients and healthcare workers. **Abtrace** The NHS is under immense pressure. Primary care teams deliver more care for a larger, longer-living population with limited time and workforce capacity. Improving health outcomes at scale requires healthcare to be more proactive, preventative, and operationally efficient. We must automate wherever possible, and thoughtfully digitise the rest. Abtrace supports over 500 primary care practices across the UK, serving 6 million people. We automate the delivery of measurements, vaccinations, blood tests, reviews, and other routine care. We improve healthcare outcomes, reduce operational burden, and create better experiences for both staff and patients. Healthcare professionals deserve software that is reliable, safe, modern, thoughtful, and well designed. Deep analytics and robust data infrastructure are the bedrock of that work – it's how we understand what's working, where opportunities to improve care are, and how we get better. **Role Overview** We're hiring our first dedicated Data Engineer to build the foundation our analytics and product teams depend on. Today, our data flows through a mix of warehouse tables and external sources that have evolved alongside the business. As we scale to support more practices and more sophisticated analysis, we need someone to shape this into a clean, centralised, well-governed platform - reliable, easy to build on, and trusted across the company. This is a senior individual-contributor role. You'll be hands-on day to day – writing pipelines, models, and infrastructure – while owning the architectural direction as we build the foundations of our data platform. Ideally you've watched data infrastructure outgrow its early foundations before, and y

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