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

Apply Now

Lead Data Engineer Technology (Product, Engineering, Design) · London ·

RedCloud
City of London
3 days ago
Create job alert
Overview

About RedCloud

The global supply chain is broken—creating a $2 trillion inventory gap where essential consumer goods fail to reach the people who need them. Brands miss sales, distributors mismanage stock, and retailers face empty shelves. The result? Higher prices, slower growth, and lost opportunity across the board.

RedCloud is fixing this. Our RedAI digital trading platform, bulk and retail trading exchanges connect key parts of the supply chain—enabling bulk inventory exchange, streamlined digital payments, and generating vast quantities of aggregated market data. By applying AI and machine learning techniques, we deliver predictive market insight and trading recommendations straight back to the trading environment—facilitating smarter everyday business decisions for our customers, from factory to warehouse to store.

Headquartered in London, RedCloud became a publicly listed company on Nasdaq (RCT) in March 2025. With a diverse team spanning many nationalities and operations across Africa, the Middle East, Europe, and Latin America. We’re building a more connected and efficient global trade network. Our AI labs are busy exploring the next generation of smart AI agents and deeper FMCG market intelligence for the benefit of our customers across a growing operational footprint.

The role

The role: A Lead Data Engineer builds, maintains and supports our data warehouse, delivering data to the whole business in an easy, performant and readable format. They are the core engineers that empower the data behind our AI strategies and business decisions. They will work in a squad alongside data scientists and AI engineers allowing for a whole picture on how the data is used. The ideal candidate will have technical skills across SQL, Database Design (Snowflake, PostgreSQL, MySQL) and Python.

What you will be doing
  • Architect Data Warehouse: Own the architecture and flow of data into our data warehouse through collaboration with the squad, other squads and the wider business. Partner with the product manager to support and deliver a data warehouse that is performant, readable, easy to use and enables the business needs of other teams.
  • Design, Build and Maintain ELT Solutions: Design, build and maintain systems to consume data from other internal RedCloud systems and external partners and/or customers.
  • Deliver Data Insights: Work with colleagues through the business and directly with customers helping them to understand the data we have, build and refine models to help them deliver impact, carry out change or drive additional revenue through our customer base.
  • Resolve Bugs: Investigate and resolve bugs in our systems.
  • Handle Production Outages / Issues: Respond to production outages and issues in our systems.
  • Estimate Features / Bugs: Estimate features and bugs within estimation sessions alongside the team.
  • Refine Feature Requirements: Refine features delivered by product managers.
  • Carry out Code Reviews: Carry out code reviews / pull-request reviews for other engineers, ensuring quality on code.
  • Keeping Pace with Technology: As a senior member of the squad, train and learn latest technologies adopted by RedCloud, suggesting future libraries and patterns we should be looking at as a business.
  • Soft Skills: Mentor members of the team and maintain effective communication within the team and across the business.
  • Mentor Members of the Team: Mentor all levels of engineers and new starters in the team, acting as a RedCloud buddy. Ensure they have all they need to succeed within your team.
  • Communication: Communicate effectively and clearly to those within your team and across the business.

Qualifications

The description notes a preference for experience with SQL, database design (Snowflake, PostgreSQL, MySQL), and Python. Other expectations include leadership in data engineering, collaboration with product management, and a willingness to mentor and guide teammates. Please apply even if you do not meet every requirement, as diverse experiences are valued.

Benefits

Working with a pioneering provider of eCommerce solutions, you will join an international company with significant growth. We encourage ambition and creativity.

Plus, you will get:

  • 25 Days Annual Leave, increasing to 26 days after 12 months
  • Enhanced Company Pension (Matched up to 5% & Salary Sacrifice)
  • Healthcare Cashplan with Medicash
  • Private Healthcare with Aviva
  • Life Insurance with AIG
  • Happl, a benefit platform with access to pre-negotiated discounts on services including entertainment, food, and fitness
  • Stock / Equity

Note: Check out messages from our CEO about growth plans and our mission as part of the application journey.


#J-18808-Ljbffr

Related Jobs

View all jobs

Senior/Lead Data Engineer

Lead Data Engineer

Lead Data Engineer

Lead Data Engineer

Lead Data Engineer

Lead Data Engineer – Data Warehousing & Analytics

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.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.