Data Engineer

Spencer Scott - Technology Recruitment

Greater London

Hybrid

GBP 65,000 - 90,000

Full time

34 hours ago
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Benefits offered by this job

Bonus scheme (generous)
Pension 14%
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-based HealthTech company advancing healthcare with AI and data-driven solutions. You will design, build, and maintain data infrastructure, working with data science, analytics and engineering teams to ensure robust, scalable data systems and secure data handling.

You will contribute to automation initiatives, building tools to streamline manual tasks, and collaborate across multidisciplinary teams to improve delivery quality,

Qualifications

  • 3+ years Data Engineering experience.
  • Strong data modelling across relational and analytical data.
  • Experience building ELT data pipelines.
  • Experience designing scalable infrastructure and automating data processes.
  • Healthcare/Life Sciences data experience is highly desirable.

Responsibilities

  • Design, develop, and maintain data infrastructure for healthcare AI/automation initiatives.
  • Collaborate with data science, analytics, and engineering teams to ensure robust, scalable data systems.
  • Develop automation tools to streamline manual and repetitive tasks.
  • Improve delivery quality, productivity, and cost efficiency across the team.

Skills

Data Engineering
Data Modelling
ELT Pipelines
Git/Azure DevOps
CI/CD

Tools

Azure DevOps

Job description

Azure Data Engineers wanted by a London based HealthTech company at the forefront of revolutionising healthcare through cutting-edge AI / Automation technology and data-driven solutions.

Their mission is to improve patient outcomes and streamline healthcare processes by leveraging the power of data. As an Azure Data Engineer, you will play a crucial role in designing, developing, and maintaining the data infrastructure. Working closely with data science, analytics and engineering teams to ensure that data systems are robust, scalable and secure.

In this role, you will contribute to a broad portfolio of automation and engineering initiatives that support both client-facing projects and the creation of scalable internal solutions. Working collaboratively with multidisciplinary teams, you will design, build, and enhance automation tools that streamline manual and repetitive tasks.

The position combines practical engineering expertise with a focus on continuous improvement, innovation, and operational efficiency. By developing reliable, user-friendly, and effective solutions, you will help improve delivery quality, increase productivity, and reduce costs across the team.

  • 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.

Package: Generous Bonus Scheme, 14% Pension, Flexible hours, Training Fund, Life Assurance, Private Medical Insurance, Volunteering, Electric Car Scheme..

Working on a hybrid model, the team goes on-site 2 days a week in the modern Central London hub. Your colleagues will also be on-site, so there is some meaning, collaboration and meaning. It will be a 2 stage interview process, which has been designed to be as quick and pain free as possible.

Spencer Scott Ltd is an equal opportunity Recruitment Agency, which means we do not discriminate on the basis of race, colour, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression. We celebrate diversity and are committed to creating inclusive working environments for all our clients.

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