National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Senior Data Engineer Lead to oversee critical data engineering activities within the Digital Health sector

S.i. Systems
London
8 months ago
Applications closed

Related Jobs

View all jobs

data technical specialist submarines

Senior Data Engineer

Data Scientist

Data Scientist

Senior Data Engineer

Senior Data Engineer

Our valued professional services client client is seeking aSenior Data Engineer Team Lead to oversee critical data engineering activities within the Digital Health sector.

10 month contract (with possible extension), % Remote

Responsibilities:

Provide strategic oversight of data engineering activities, shaping platform strategy and data architecture. Act as a technical leader for the team, establishing best practices for data engineering. Collaborate with senior leadership and external stakeholders as the senior technical resource for the group. Monitor and optimize ARC platform data pipelines to ensure efficient data flow and system performance. Work with stakeholders and data SMEs to identify and implement enhancements to ARC platform capabilities. Conduct advanced data profiling and quality assessments to ensure data health and integrity. Implement and manage data access policies in coordination with the Data Governance and Engineering team. Troubleshoot and resolve data-related issues in collaboration with operational support teams. Work with source systems to identify and transport necessary data, using methodologies such as SQL, NoSQL, and RESTful. Document data extraction processes, optimizations, and enhancements for reference and compliance. Apply and update classifications for personal health information (PHI) data elements as required. Provide custom data quality rules and conduct associated scans on the data estate. Facilitate access to draft materials and ensure feedback is obtained prior to final delivery. Produce comprehensive documentation for data pipeline optimizations, operational support, and user training materials. Write status reports outlining completed activities and outstanding issues or risks.

Must Have Skills:

7+ years of experience in data engineering, with at least 3 years in a team lead or technical leadership role. Experience withdata profiling,quality assessments, andgovernance policies (Master Data Management).Strong knowledge of data pipeline optimization and data architecture. Proficiency in SQL, NoSQL, and RESTful methodologies.

Nice to Have Skills:

Familiarity with data security and compliance regulations related to personal health information (PHI). Knowledge of data integration tools and techniques.
National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Get a Better Machine Learning Job After a Lay-Off or Redundancy

Redundancy in machine learning can feel especially frustrating when your role was technically advanced, strategically important, or AI-facing. But the UK still has strong demand for machine learning professionals across fintech, healthtech, retail, cybersecurity, autonomous systems, and generative AI. Whether you're a research-oriented ML engineer, production-focused MLOps developer, or applied scientist, this guide is designed to help you bounce back from redundancy and find a better opportunity that suits your goals.

Machine Learning Jobs Salary Calculator 2025: Figure Out Your True Worth in Seconds

Why last year’s pay survey is useless for UK ML professionals today Ask a Machine Learning Engineer wrangling transformer checkpoints, an MLOps Lead firefighting drift alarms, or a Research Scientist training diffusion models at 3 a.m.: “Am I earning what I deserve?” The honest answer changes monthly. A single OpenAI model drop doubles GPU demand, healthcare regulators release fresh explainability guidance, & a fintech unicorn pays six figures for vector‑search expertise. Each shock nudges salary bands. Any PDF salary guide printed in 2024 now looks like an outdated Jupyter notebook—missing the gen‑AI tsunami, the surge in edge inference, & the UK’s new Responsible‑AI framework. To give ML professionals an accurate benchmark, MachineLearningJobs.co.uk distilled a transparent, three‑factor formula that estimates a realistic 2025 salary in under a minute. Feed in your discipline, UK region, & seniority; you’ll receive a defensible figure—no stale averages, no guesswork. This article unpacks the formula, highlights the forces driving ML pay skyward, & offers five practical moves to boost your value inside the next ninety days.

How to Present Machine Learning Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.