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For Companies At a Glance
- Tasks: Design, build, and maintain data infrastructure for our Machine Learning team.
- Company: Epic Games creates award-winning games and innovative engine technology globally.
- Benefits: Enjoy 100% paid benefits, including health insurance, dental, and mental well-being programs.
- Why this job: Join a collaborative team that values innovation and community impact in tech.
- Qualifications: BSc/MSc in Computer Science or extensive hands-on experience; strong analytical skills required.
- Other info: Epic Games promotes diversity and inclusivity in the workplace.
The predicted salary is between 42000 - 84000 £ per year.
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 ENGINEERING
What 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 .
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Machine Learning Data Engineer employer: Houston Texans
Contact Detail:
Houston Texans Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Data Engineer
✨Tip Number 1
Familiarize yourself with AWS and its services, as this role heavily relies on managing AWS infrastructure. Consider taking online courses or certifications to deepen your understanding of cloud computing and data management.
✨Tip Number 2
Gain hands-on experience with ETL processes and tools like Apache Airflow. Building a small project that involves data extraction, transformation, and loading can showcase your skills and understanding of the data pipeline.
✨Tip Number 3
Brush up on your SQL skills, especially in writing custom procedures. Practice by working on sample databases or contributing to open-source projects that require database management.
✨Tip Number 4
Network with professionals in the data engineering field through platforms like LinkedIn. Engaging with others can provide insights into the industry and may lead to referrals or recommendations for the position.
We think you need these skills to ace Machine Learning Data Engineer
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities and requirements of the Machine Learning Data Engineer position. Tailor your application to highlight relevant experiences that align with the job description.
Highlight Relevant Skills: In your CV and cover letter, emphasize your experience with ETL processes, data modeling, and AWS. Mention specific projects where you've designed or maintained data infrastructure, as this will resonate with the hiring team.
Showcase Your Analytical Background: If you have a degree in Computer Science or related fields, mention it prominently. If not, focus on your hands-on experience and any relevant certifications that demonstrate your analytical skills and technical expertise.
Craft a Compelling Cover Letter: Use your cover letter to tell a story about your passion for data engineering and how it aligns with Epic's mission. Discuss your collaborative experiences and how you can contribute to their innovative environment.
How to prepare for a job interview at Houston Texans
✨Showcase Your Analytical Skills
Be prepared to discuss your analytical background and how it relates to the role. Highlight any relevant projects or experiences that demonstrate your ability to design and implement data solutions, especially in ETL processes.
✨Demonstrate Your Technical Expertise
Familiarize yourself with the technologies mentioned in the job description, such as AWS, SQL, and Python. Be ready to answer technical questions and possibly solve problems on the spot to showcase your hands-on experience.
✨Understand the Company Culture
Epic values collaboration and innovation. Research their projects and be prepared to discuss how you can contribute to their mission. Show enthusiasm for being part of a team that strives to enhance user experiences.
✨Prepare Questions About Data Infrastructure
Think of insightful questions regarding their data infrastructure and how it supports machine learning initiatives. This shows your interest in the role and helps you understand how you can fit into their existing systems.
