Senior Data Engineer

About us

uMed is a healthtech and data platform advancing clinical research through high-quality real-world and patient-generated data. uMed combines RWE with the power of patient-generated data to address the evidence gaps in life science research. We build secure, scalable data platforms that transform complex patient, survey, and clinical data into actionable insights for researchers, clinicians, and partners.

As a Senior Data Engineer, you will be responsible for designing, building, and operating uMed’s core data pipelines, data warehouse layers, and analytics-ready datasets. During this phase of growth, you will be the primary Data Engineer, requiring a high degree of autonomy, technical judgement, and ownership.

You will also act as line manager for a mid-level Data Engineer (which will also be a new role), providing hands‑on technical mentorship, day‑to‑day guidance, and code review, while remaining deeply involved in data pipeline delivery.

You will work in close partnership with the Product Architect, Enterprise Data, who owns the enterprise data models and long‑term data design, and collaborate closely with the Data Platform Engineer, who owns cloud infrastructure, environments, and Dev Ops.

You will support data across the UK and US regions, ensuring data is reliable, compliant, and fit for analytics, insights, and AI‑driven use cases.

Architectural ownership of enterprise data models sits with the Product Architect, Enterprise Data, while the Senior Data Engineer owns the implementation, reliability, and evolution of data pipelines and analytics‑ready datasets.

Data Engineering & Pipelines

• Design, build, and maintain scalable, reliable data pipelines for structured and semi‑structured data (e.g. surveys, EHR extracts, events, and operational systems).
• Own end‑to‑end delivery of ETL/ELT pipelines from source ingestion through to analytics‑ready outputs.
• Ensure pipelines are performant, cost‑efficient, observable, and production‑grade.

Data Modelling & Analytics Enablement

• Partner closely with the Product Architect, Enterprise Data, on data modelling and design, contributing implementation expertise and feedback from real‑world usage.
• Translate canonical and logical data models into performant physical models in the analytics warehouse.
• Implement transformations that support cross‑study, cross‑drug, and cross‑region (UK and US) analytics and comparisons.
• Deliver reusable, well‑documented datasets aligned with a Data as a Product approach.

Data Quality, Governance & Compliance

• Implement data quality checks, validation rules, and reconciliation processes across data sources.
• Ensure datasets and pipelines comply with regional data protection and regulatory requirements (e.g. UK GDPR, US HIPAA, where applicable).
• Maintain clear documentation, data lineage, and auditability in line with enterprise standards.

Cloud & Platform Collaboration

• Build and operate data pipelines on AWS (e.g. S3, Redshift, RDS, Athena, Document
  
  DB).
• Partner closely with the Data Platform Engineer to align data pipelines with platform infrastructure, environment configuration, access controls, and deployment patterns.
• Collaborate on well‑scoped data development tasks where shared context or operational efficiency makes sense, while maintaining clear ownership boundaries.

Analytics, Insights & AI Enablement

• Work with Analytics and Product teams to enable dashboards, reporting, and insight generation (e.g. Zoho Analytics or equivalent BI tools).
• Ensure data structures support dynamic filtering, comparisons, and narrative or AI‑driven insights.
• Support downstream AI/ML and insight‑generation use cases with clean, well‑structured data.

Collaboration & Technical Leadership

• Act as a senior technical contributor and mentor as the data function grows.
• Line manage and mentor a mid‑level Data Engineer, supporting their technical growth and ensuring high‑quality delivery.
• Promote best practices in data engineering, testing, documentation, and code quality.
• Communicate clearly with the product team and relevant engineering stakeholders to translate requirements into robust data solutions.

Core Requirements

• 7+ years…