Health Data Engineer - Azure Analytics, Hybrid

Lane Clark & Peacock LLP.; Greater London, Winchester; Hybrid; GBP 70,000 - 100,000; Full time

Benefits offered by this job

Hybrid working

Professional study support

Life assurance

Income protection

Private medical insurance

Cycle to work

Job summary

Lane Clark & Peacock LLP is seeking a Health Data Engineer (Associate Consultant) to scale analytics delivery in our Health team in London or Winchester. The role focuses on constructing analytical databases from client data and building robust data infrastructure in a hybrid setup.

You will work with clinicians, analysts and health economists to turn complex requirements into practical engineering solutions, with emphasis on Azure-based data engineering and automation.

Qualifications

• Minimum 2:1 degree in Computer Science, Software Engineering, or related discipline.
• Likely 3+ years in data engineering within UK healthcare or life sciences.
• Experience with Azure Cloud Services, especially Data Factory, Databricks, SQL databases.

Responsibilities

• Design and implement analytical data models for health data.
• Build and maintain analytical databases integrating structured and unstructured data.
• Develop robust data infrastructure and scalable pipelines.
• Automate workflows across data processing, management, and reporting.
• Collaborate with clinicians, analysts and epidemiologists to translate requirements into engineering solutions.
• Support cloud architecture, particularly Azure, for performance and resilience.

Skills

SQL

Python

ELT pipelines

Azure Data Factory

Databricks

CI/CD

Git

AI/LLM tooling

Testing & monitoring

Documentation

Education

2:1 in Computer Science or related field

Tools

Azure Databricks

SQL Server/Databases

Azure DevOps

Job description

Lane Clark & Peacock LLP is seeking a Health Data Engineer (Associate Consultant) to scale analytics delivery in our Health team in London or Winchester. The role focuses on constructing analytical databases from client data and building robust data infrastructure in a hybrid setup.

You will work with clinicians, analysts and health economists to turn complex requirements into practical engineering solutions, with emphasis on Azure-based data engineering and automation.