Machine Learning Data Engineer (Basé à London)

Jobleads
Holloway
1 week ago
Create job alert

WHAT MAKES US EPIC?

At the core of Epic’s success are talented, passionate people. Epic prides itself on creating a collaborative, welcoming, and creative environment. Whether it’s building award-winning games or crafting engine technology that enables others to make visually stunning interactive experiences, we’re always innovating.

Being Epic means being a part of a team that continually strives to do right by our community and users. We’re constantly innovating to raise the bar of engine and game development.

DATA ENGINEERINGWhat We Do

Our mission is to provide a world-class platform that empowers the business to leverage data that will enhance, monitor, and support our products. We are responsible for data ingestion systems, processing pipelines, and various data stores all operating in the cloud. We operate at a petabyte scale, and support near real-time use cases as well as more traditional batch approaches.

What You'll Do

You will be responsible for designing, building, and maintaining our data infrastructure to ensure the reliability and efficiency of our data and systems used by our Machine Learning team. Your role will include creating and maintaining data pipelines that transform and load data from various products and managing the AWS infrastructure for our machine learning platform. Additionally, you will work with engineers, product managers, and data scientists to design and implement robust and scalable data services that support Epic's mission while ensuring our user’s privacy.

In this role, you will

  • Interact with product teams to understand how our safety systems interact with their data systems.
  • Design and implement an automated end-to-end ETL process, including data anonymization, to prepare data for machine learning and ad hoc analysis.
  • Manage and scale the tools and technologies we use to label data running on AWS.
  • Devise database structure and technology for storing and efficiently accessing large data sets (millions of records) of different types (text, images, videos, etc.).
  • Use and implement data extraction APIs.
  • Write and invoke custom SQL procedures.
  • Support data versioning strategies using automated tools.

What we're looking for

  • Strong analytical background: BSc or MSc in Computer Science/Software Engineering or related subject - candidates without a degree are welcome as long as they have extensive hands-on experience.
  • Experience in ETL technical design, automated data quality testing, QA and documentation, data warehousing, and data modeling.
  • Experience with Python for interaction with Web Services (e.g., Rest and Postman).
  • Experience with using and developing data APIs.
  • Experience using AWS, Snowflake, or other comparable large-scale analytics platforms.
  • Experience monitoring and managing databases (we use Elasticsearch / MongoDB / PostgreSQL).
  • Experience with SQL.
  • Experience with data versioning tools.
  • Experience developing and maintaining data infrastructure for ETL pipelines, such as Apache Airflow.

EPIC JOB + EPIC BENEFITS = EPIC LIFE

We pay 100% for benefits except for PMI (for dependents). Our current benefits package includes pension, private medical insurance, health care cash plan, dental insurance, disability and life insurance, critical illness, cycle to work scheme, flu shots, health checks, and meals. We also offer a robust mental well-being program through Modern Health, which provides free therapy and coaching for employees & dependents.

ABOUT US

Epic Games spans across 25 countries with 46 studios and 4,500+ employees globally. For over 25 years, we've been making award-winning games and engine technology that empowers others to make visually stunning games and 3D content that bring environments to life like never before. Epic's award-winning Unreal Engine technology not only provides game developers the ability to build high-fidelity, interactive experiences for PC, console, mobile, and VR, it is also a tool being embraced by content creators across a variety of industries such as media and entertainment, automotive, and architectural design. As we continue to build our Engine technology and develop remarkable games, we strive to build teams of world-class talent.

Like what you hear? Come be a part of something Epic!

Epic Games deeply values diverse teams and an inclusive work culture, and we are proud to be an Equal Opportunity employer. Learn more about our Equal Employment Opportunity (EEO) Policy here.

#J-18808-Ljbffr

Related Jobs

View all jobs

Data Engineer (5 Months Fixed Term Contract)

Data Engineer / Analytics Engineer

AI Engineer / Data Scientist

Geospatial Data Engineer

Remote Azure Data Engineer (Contract)

AWS Lead Data Engineer

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.

Data Science Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Data science has become one of the most sought‑after fields in technology, leveraging mathematics, statistics, machine learning, and programming to derive valuable insights from data. Organisations across every sector—finance, healthcare, retail, government—rely on data scientists to build predictive models, understand patterns, and shape strategy with data‑driven decisions. If you’re gearing up for a data science interview, expect a well‑rounded evaluation. Beyond statistics and algorithms, many roles also require data wrangling, visualisation, software engineering, and communication skills. Interviewers want to see if you can slice and dice messy datasets, design experiments, and scale ML models to production. In this guide, we’ll explore 30 real coding & system‑design questions commonly posed in data science interviews. You’ll find challenges ranging from algorithmic coding and statistical puzzle‑solving to the architectural side of building data science platforms in real‑world settings. By practising with these questions, you’ll gain the confidence and clarity needed to stand out among competitive candidates. And if you’re actively seeking data science opportunities in the UK, be sure to visit www.datascience-jobs.co.uk. It’s a comprehensive hub featuring junior, mid‑level, and senior data science vacancies—spanning start‑ups to FTSE 100 companies. Let’s dive into what you need to know.

Negotiating Your Data Science Job Offer: Equity, Bonuses & Perks Explained

Data science has rapidly evolved from a niche specialty to a cornerstone of strategic decision-making in virtually every industry—from finance and healthcare to retail, entertainment, and AI research. As a mid‑senior data scientist, you’re not just running predictive models or generating dashboards; you’re shaping business strategy, product innovation, and customer experiences. This level of influence is why employers are increasingly offering compensation packages that go beyond a baseline salary. Yet, many professionals still tend to focus almost exclusively on base pay when negotiating a new role. This can be a costly oversight. Companies vying for data science talent—especially in the UK, where demand often outstrips supply—routinely offer equity, bonuses, flexible work options, and professional development funds in addition to salary. Recognising these opportunities and effectively negotiating them can have a substantial impact on your total earnings and long-term career satisfaction. This guide explores every facet of negotiating a data science job offer—from understanding equity structures and bonus schemes to weighing crucial perks like remote work and ongoing skill development. By the end, you’ll be well-equipped to secure a holistic package aligned with your market value, your life goals, and the tremendous impact you bring to any organisation.