Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Engineer - GSK0JP00107167

Experis - ManpowerGroup
City of London
2 days ago
Create job alert
Overview

Data Engineer
Pay: £887.63
Term: 6 months (potential extension)
Location: Kings Cross, or Stevenage (depending on preference)

Our pharmaceutical client see a world in which advanced applications of Machine Learning and AI will allow them to develop novel therapies to existing diseases and to quickly respond to emerging or changing diseases with personalized drugs, driving better outcomes at reduced cost with fewer side effects. It is an ambitious vision that will require the development of products and solutions at the cutting edge of Machine Learning and AI. They\'re looking for a highly skilled data engineer to help us make this vision a reality.

Strong candidates will have a track record of shipping data products derived from complex sources, responsible for the process from conceptual data pipelines to production scale. We have a commitment to quality, so successful candidates will be able to use modern cloud tooling and techniques to deliver reliable data pipelines and continuously improve them.

This role requires a passion for solving challenging problems aligned to exciting Artificial Intelligence and Machine Learning applications. Educational or professional background in the biological sciences is a plus but is not necessary; passion to help therapies for new and existing diseases, and a pattern of continuous learning and development is mandatory.

Responsibilities
  • Build data pipelines using modern data engineering tools on Google Cloud: Python, Spark, SQL, BigQuery, Cloud Storage
  • Ensure data pipelines meet the specific scientific needs of data consuming applications
  • Responsible for high quality software implementations according to best practices, including automated test suites and documentation
  • Develop, measure, and monitor key metrics for all tools and services and consistently seek to iterate on and improve them
  • Participate in code reviews, continuously improving personal standards as well as the wider team and product
  • Liaise with other technical staff and data engineers in the team and across allied teams, to build an end-to-end pipeline consuming other data products
Basic qualifications
  • 2+ years of data engineering experience with a Bachelors degree in a relevant field (including computational, numerate or life sciences), or equivalent experience
  • Cloud experience (e.g. Google Cloud preferred)
  • Strong skills with industry experience in Python and SQL
  • Unit testing experience (e.g. pytest)
  • Knowledge of agile practices and able to perform in agile software development environments
  • Strong experience with modern software development tools / ways of working (e.g. git/GitHub, DevOps tools for deployment)
Preferred qualifications
  • Demonstrated experience with biological or scientific data (e.g. genomics, transcriptomics, proteomics), or pharmaceutical industry experience
  • Bioinformatics expertise, familiarity with large scale bioinformatics datasets
  • Experience using Nextflow pipelines
  • Knowledge of NLP techniques and experience of processing unstructured data, using vector stores, and approximate retrieval
  • Familiarity with orchestration tooling (e.g. Airflow or Google Workflows)
  • Experience with AI/ML powered applications
  • Experience with Docker or containerized applications


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

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.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.

Why the UK Could Be the World’s Next Data Science Jobs Hub

Data science is arguably the most transformative technological field of the 21st century. From powering artificial intelligence algorithms to enabling complex business decisions, data science is essential across sectors. As organisations leverage data more rapidly—from retailers predicting customer behaviour to health providers diagnosing conditions—demand for proficiency in data science continues to surge. The United Kingdom is particularly well-positioned to become a global data science jobs hub. With world-class universities, a strong tech sector, growing AI infrastructure, and supportive policy environments, the UK is poised for growth. This article delves into why the UK could emerge as a leading destination for data science careers, explores the job market’s current state, outlines future opportunities, highlights challenges, and charts what must happen to realise this vision.