Lead Data Engineer

Uniting Ambition
West Midlands
1 week ago
Create job alert

We are looking for an experienced Lead Engineer to lead a high-performing Data Engineering team building scalable data and reporting platforms used by global stakeholders.


In this role, you will guide the development of high-throughput, database-centric applications that process and deliver critical operational data at scale. Working within a cloud-first architecture on Google Cloud Platform (GCP), you will play a key role in designing and delivering modern data solutions using BigQuery and distributed systems.


You will lead a geographically distributed team and collaborate with stakeholders across the business to deliver reliable, high-performance data platforms that support a global client base.


This role is eligible for hybrid working in the North West or Midlands


About the Team

The Data Engineering team builds and maintains large-scale data systems designed for performance, reliability, and efficiency.


Our platform includes:



  • BigQuery data warehousing
  • High-throughput distributed applications
  • Integration with REST and SOAP APIs
  • Windows and web services
  • Web-based applications and reporting platforms

As Lead Engineer, you will drive technical delivery while helping evolve the team’s cloud and data capabilities.


What You’ll Be Doing

  • Leading and mentoring a geographically distributed Data Engineering team
  • Driving the development of cloud-based data and reporting solutions on GCP
  • Owning the delivery of scalable data platforms that support global operations
  • Supporting the adoption of AI tools and automation to enhance engineering workflows
  • Collaborating with stakeholders across multiple departments to prioritise and deliver projects
  • Managing technical risks, issues, and cross-team dependencies
  • Improving engineering practices, processes, and delivery efficiency
  • Ensuring high standards of system performance, scalability, and reliability

Skills and Experience

  • Strong experience with Google Cloud Platform (GCP) and BigQuery
  • Deep understanding of cloud architecture and distributed data systems
  • Commercial database development experience using SQL Server, T‑SQL, BigQuery or GoogleSQL
  • Experience implementing data platforms, reporting systems, or large-scale data pipelines
  • Experience working with AI tools to improve development workflows
  • Experience designing and implementing cloud-native solutions
  • Experience working with large-scale global data platforms is advantageous


#J-18808-Ljbffr

Related Jobs

View all jobs

Lead Data Engineer

Lead Data Engineer

Lead Data Engineer

Lead Data Engineer

Lead Data Engineer (AWS & Snowflake)

Lead Data/Head of 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.

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.