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

Apply Now

Data Engineer

La Fosse Associates
City of London
1 week ago
Create job alert
Overview

Data Engineer –


London (Hybrid)


£75k – £95k


La Fosse has partnered with an exciting Gaming company to hire a Data Engineer for their UK team. This hybrid role is based in London (1–2 days in office) and offers the opportunity to work on a first-of-its-kind project with huge business impact.


Responsibilities

Role Overview:


As the Data Engineer on this project, you will work closely with a cross-functional team of software and data engineers to build large-scale data systems supporting thousands of daily users. You’ll focus on designing, building, and maintaining ETL/ELT pipelines, integrating data from multiple sources into Snowflake and downstream tools, and developing proofs of concept to optimise delivery.


This role provides ownership of technologies and solutions, allowing you to propose and implement innovative approaches while influencing project architecture.


Technical Responsibilities:



  • Design, build, and maintain scalable ETL/ELT pipelines.
  • Integrate data from external APIs and internal systems into Snowflake.
  • Support data aggregation and integration to enable commercial decision-making.
  • Propose technical solutions, proofs of concept, and best practices.
  • Work with messaging and scheduling tools (e.g., Kafka, Airflow).
  • Apply Python and SQL expertise for complex data processing.
  • Contribute to IaC/DevOps practices (Terraform, CI/CD pipelines, containerisation).
  • Leverage AI tools to improve workflow efficiency and reduce cycle times.

Qualifications

  • 4+ years’ experience in Data or Software Engineering, ideally with hands-on experience in data infrastructure.
  • Strong expertise in Snowflake (certifications a plus).
  • Experience building or maintaining scalable data systems and integrations.
  • Strong programming skills in Python and SQL (OOP, not just scripting).
  • Experience with ETL/ELT orchestration, data modelling, and cloud-based platforms (AWS preferred).
  • Comfortable collaborating with software engineers, analysts, and product managers.
  • Proactive problem solver with examples of owning solutions or projects.
  • Interested in working in the gaming or sports betting industry.

If you are a technically strong, solutions-focused Data Engineer ready to take ownership and deliver impact, we would love to hear from you. Apply now to join the team!


#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.

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.