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uMed

Data Engineer

Remote

United kingdom

Junior

Full Time

06-02-2026

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Skills

Python Tableau SQL Data Engineering Monitoring Research power bi AWS Analytics

Job Specifications

About Us

uMed is a healthtech and data platform advancing clinical research through high-quality real-world and patient-generated data. We build secure, scalable data platforms that transform complex patient, survey, and clinical data into actionable insights for researchers, clinicians, and partners.

Who We Are Looking For

As a Data Engineer, you will support the development and operation of uMed's data pipelines and analytics-ready datasets. You will work closely with the Senior Data Engineer, who will provide technical guidance and mentorship while offering opportunities to grow your skills in data ingestion, transformation, and analytics enablement.

This role is ideal for someone who enjoys building reliable data pipelines and wants to deepen their experience working on a modern, AWS-based data platform.

Requirements

Data Engineering & Pipelines

Build and maintain data pipelines for structured and semi-structured data (e.g., surveys, EHR extracts, events, and operational systems)
Support ETL/ELT workflows from source ingestion through to analytics-ready outputs
Troubleshoot pipeline failures and data issues, escalating and collaborating where needed

Data Modelling & Analytics Support

Implement data transformations and models based on designs and guidance from the Senior Data Engineer and Product Architect
Help maintain analytics-ready datasets in the data warehouse to support reporting and insights
Contribute to datasets that support cross-study and cross-region (UK and US) analysis

Data Quality & Reliability

Assist in implementing data quality checks and validation rules
Help investigate data discrepancies and ensure data accuracy and consistency
Contribute to documentation and data lineage as part of standard delivery

Collaboration & Learning

Work closely with the Senior Data Engineer through code reviews, pairing, and technical feedback
Collaborate with product and analytics teams to understand data requirements
Follow and apply established best practices in data engineering, testing, and documentation

Required Qualifications

Core Requirements

3-4 years of experience in data engineering or closely related roles
Solid SQL skills and experience working with analytics-focused datasets
Experience building or maintaining data pipelines in a cloud environment (AWS preferred)
Familiarity with semi-structured data (e.g., JSON, event data)

Technical Stack (Experience With Some Of The Following)

AWS: S3, Redshift, RDS, Athena, DocumentDB (or equivalent)
Data transformation tools (e.g., dbt or similar)
Orchestration tools (e.g., Airflow, Step Functions, or similar)
Python (or similar) for data processing and automation
BI tools and analytics enablement (e.g., Zoho Analytics, Tableau, Power BI, or similar)

Nice to Have

Experience in healthcare, clinical research, or regulated data environments
Exposure to data quality frameworks or monitoring
Experience working with multi-region data platforms (UK and US)
Interest in analytics, insights, or AI-enabled data products

Why Join Us?

Work on real-world healthcare data to make a meaningful impact
Gain experience across the full data lifecycle, from ingestion to analytics
Join a collaborative team building a growing data platform

Benefits

25 days' holiday, plus your birthday off and bank holidays on top

Private healthcare through Vitality

2 paid volunteering days per year

A monthly allowance to spend via our flexible benefits portal

One day a week working from a coworking space of your choice, if you want to mix up working from home

Equipment setup allowance to make your home office work for you

Enhanced maternity, paternity, and parental leave

About the Company

uMed combines RWE with the power of patient generated data to address the evidence gaps in life science research. By leveraging uMed's ACCESS Research Platform which is embedded across a global network of healthcare institutions, researchers can rapidly access and engage with patients to generate insights derived from the decentralised collection of electronic health records, clinical outcomes, patient-reported data and biosamples. Know more