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

Apply Now

Data Engineer

Legend
City of London
1 month ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

About Legend

Legend is quietly building #1 products that make noise in the most competitive comparison markets in the world: iGaming, Sports Betting, Personal Finance. We exist to build better experiences. From amplified career paths to supercharged online journeys for our people and our users, we deliver magic rooted in method. With over 500 Legends and counting, we’re helping companies turbocharge their brand growth in over 18 countries worldwide. If you’re looking for a company with momentum and the opportunity to progress at pace, Legend has it. Unlock the Legend in you.

The Role

Legend is hiring a Data Engineer, reporting directly to our Head of Data Engineering. In this role, you will have the possibility to build and contribute to data products and platform functionalities that tangibly serve the business with the freedom to build and experiment. At Legend, you’ll get real ownership as a Data Engineer - our team owns its entire infrastructure, giving you true end-to-end impact. If you want to be part of a team that builds data platforms with the freedom to experiment with new tools and approaches, you’ll thrive here. We value innovation with purpose, so you can help shape the future of our data products. In this role, we value diverse perspectives and encourage you to apply even if you don\'t meet every qualification listed.

Your Impact
  • Contribute to improvements to the data infrastructure required by the teams that consume data.
  • Contribute to improvements to the processes and data pipelines that collect data from operational data sources and external data producers, normalise, standardise, and enrich them, and make them available to data consumers in an accessible and discoverable manner.
  • Contribute to and improve the data security measures in place to make sure data consumers can access the data they need, but only what they need and not more.
  • Make sure the produced data adheres to data quality measures and SLAs that make it appropriate to use by consumers
  • Liaise with internal data producers and consumers to satisfy business requirements on a daily basis
What You\'ll Bring
  • Good foundational familiarity with Snowflake (or an equivalent modern cloud data warehouse tool) and data modeling skills for analytical/transactional data systems
  • Managing cloud infrastructure, networking, and security on AWS using Terraform
  • Good foundational knowledge about workflow orchestrators, specifically Airflow or Dagster
  • Good knowledge of Python and using Python to build data pipelines.
  • Knowledge of CI/CD measures and tools, such as GitHub Actions
  • Highly preferred: working knowledge of data transformation tools such as dbt or SQLMesh.
  • Preferred: having been involved in the deployment of data governance tools such as data quality or data catalogue solutions
The Interview Process
  • 1st: Initial Chat with Talent Partner (45 mins via Zoom)
  • 2nd: Technical Interview including a Technical Assessment and Technical Discussion (1.5 hours via Zoom)
  • 3rd: Values Interview including with Technical and Non-Technical team members (1 hour video via Zoom)
  • 4th: Final interview including Technical focus with the Hiring Manager and Tech Leadership team (1 hour video via Zoom)
Why Legend
  • Super smart colleagues to work alongside and learn from.
  • Engaging development opportunities at all levels.
  • Tailored flexibility for your work-life balance.
  • Annual discretionary bonus to reward your efforts.
  • Paid annual leave PLUS a well-deserved break to recharge your batteries during the festive season! Our offices are closed between Christmas and New Year\'s, allowing you to enjoy downtime without dipping into your annual allowance.
  • Long term incentive plan so we can all share in the growth and success of Legend.
  • Exciting global Legend events, where we unite in person to ignite our shared passion and unveil the exciting strategies for the year ahead!
  • Unlock your full potential by joining the Legend team. To support you on this journey, we provide an extensive array of benefits and perks, as outlined in our global offerings above. For country specific benefits please reach out to your talent partner.


#J-18808-Ljbffr

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 Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

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.