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- Tasks: Design and develop scalable data pipelines while collaborating with talented teams.
- Company: Join Rockstar Games, a leader in world-class entertainment experiences.
- Benefits: Enjoy a fully remote role with competitive salary and growth opportunities.
- Why this job: Make an impact on game development through innovative analytics and big data.
- Qualifications: 3+ years in analytics or data engineering with strong Python skills.
- Other info: Be part of a motivated team in a dynamic and inclusive environment.
The predicted salary is between 28800 - 48000 £ per year.
At Rockstar Games, we create world-class entertainment experiences. Become part of a team working on some of the most rewarding, large-scale creative projects to be found in any entertainment medium - all within an inclusive, highly-motivated environment where you can learn and collaborate with some of the most talented people in the industry.
Rockstar Games is on the lookout for a skilled Analytics Engineer with strong software development skills who is passionate about games and big data. This is a full-time, permanent position based in Rockstar’s unique game development studio in the heart of Leeds, England.
The Rockstar Games Analytics team provides insights and actionable results to a wide variety of stakeholders across the organization in support of their decision making. We partner with multiple departments across the company, leveraging analytics to measure and improve on the success and health of our games. We collaborate as a distributed team to develop innovative data pipelines, data products, data models, reports, analyses, and machine learning applications.
The Analytics Architecture vertical within the Analytics team is tasked with building out high impact data models and internal tooling to support the wider Analytics team. Partner with Data Scientists and business stakeholders to understand analytical needs and translate them into robust data infrastructure and workflows for the global Analytics team to leverage for deriving insights. Collaborate with the Data Engineering team to design data models and data pipelines.
Key Responsibilities:
- Design, develop and maintain scalable data pipelines.
- Monitor performance and optimize data systems for high performance and reliability.
- Collaborate with the Data Integrity team to build a Data Quality Framework that ensures production data meets SLAs for key stakeholders and business processes.
- Perform timely Root Cause Analysis to troubleshoot data-related issues; assist in implementation of code and process fixes.
- Define and implement monitoring and alerting policies for data solutions.
Requirements:
- 3+ years of experience in analytics engineering or data engineering.
- Proven track record in building, monitoring, and optimizing large-scale data systems and analytics infrastructure.
Analytics Engineer - Fully Remote in Leeds employer: Rockstar Games
Contact Detail:
Rockstar Games Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Analytics Engineer - Fully Remote in Leeds
✨Tip Number 1
Network like a pro! Reach out to folks in the gaming and analytics space on LinkedIn or at industry events. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data projects, especially those related to gaming. This gives potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the gaming industry. Be ready to discuss how your experience aligns with Rockstar's mission and values.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team.
We think you need these skills to ace Analytics Engineer - Fully Remote in Leeds
Some tips for your application 🫡
Show Your Passion for Games: When writing your application, let us know why you're passionate about games and how that drives your work as an Analytics Engineer. We love seeing candidates who share our enthusiasm for the industry!
Highlight Relevant Experience: Make sure to showcase your experience in analytics engineering or data engineering, especially with Python. We want to see how your skills align with the role, so don’t hold back on those achievements!
Tailor Your Application: Take a moment to tailor your application to Rockstar Games specifically. Mention how you can contribute to our Analytics team and the exciting projects we’re working on. Personal touches go a long way!
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be part of our streamlined process, making it easier for us to connect with you!
How to prepare for a job interview at Rockstar Games
✨Know Your Data Inside Out
Make sure you brush up on your knowledge of data systems and analytics. Be prepared to discuss your experience with building and optimising data pipelines, as well as any specific projects you've worked on that relate to big data. This will show your passion for the role and your understanding of the technical requirements.
✨Showcase Your Collaboration Skills
Since the role involves working closely with Data Scientists and business stakeholders, be ready to share examples of how you've successfully collaborated in the past. Highlight any experiences where you translated analytical needs into actionable data solutions, as this will demonstrate your ability to work effectively in a team environment.
✨Prepare for Technical Questions
Expect some technical questions related to Python and data engineering. Brush up on your coding skills and be ready to solve problems on the spot. Practising common data engineering scenarios can help you feel more confident and showcase your problem-solving abilities during the interview.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions! Inquire about the current projects the Analytics team is working on or how they measure the success of their data models. This shows your genuine interest in the role and helps you understand if the company culture aligns with your values.