Azure Data Engineer – HealthTech AI & Automation (London)

Spencer Scott - Technology Recruitment; Greater London; Hybrid; GBP 90,000 - 110,000; Full time

Benefits offered by this job

Bonus scheme

14% Pension

Flexible hours

Training fund

Life assurance

Private medical insurance

Volunteering

Electric Car Scheme

Job summary

Spencer Scott Ltd is recruiting an Azure Data Engineer for a London HealthTech company pushing AI and automation in healthcare data. You will design, build and maintain data pipelines and infrastructure, collaborating with data science and analytics teams to ensure secure, scalable data solutions.

The role emphasizes automation, efficiency, and delivering reliable data platforms to support both client projects and internal initiatives. Hybrid model with on-site two days per week.

Qualifications

• 3+ years’ Data Engineering experience.
• Strong data modelling experience across relational and analytical data.
• Experience building ELT data pipelines.
• Git / Azure DevOps and CI/CD experience.
• Experience designing scalable infrastructure and automating data processes.
• Healthcare / Life Sciences experience is highly desirable, particularly experience working with sensitive or real-world health data.

Responsibilities

• Design, develop, and maintain data infrastructure and automation tools.
• Collaborate with data science, analytics and engineering teams to ensure robust, scalable and secure data systems.
• Contribute to a portfolio of automation and engineering initiatives supporting client projects and internal solutions.

Skills

Data engineering

Data modelling

ELT pipelines

Git & CI/CD

Scalable data infra

Tools

Azure DevOps

Job description

Spencer Scott Ltd is recruiting an Azure Data Engineer for a London HealthTech company pushing AI and automation in healthcare data. You will design, build and maintain data pipelines and infrastructure, collaborating with data science and analytics teams to ensure secure, scalable data solutions.

The role emphasizes automation, efficiency, and delivering reliable data platforms to support both client projects and internal initiatives. Hybrid model with on-site two days per week.