Senior Data Engineer, Player Care

You know the feeling when you’ve beaten your personal high score? Working in Analytics at Supercell is like having those moments everyday. And better yet, making the best gameplay decision is a perfect blend of intuition and data.

As a Data Engineer, you’ll be leveling up our Player Care operations. Actionable data is an integral part of providing better experience to our players and enabling both our Player Support and Trust & Safety teams to be effective and data driven. We are working towards being hypothesis driven and for that - we need your skills to help us build our data and tooling to be ready to continuously improve our service.

Picture yourself leveling up our tooling to legendary status of the highest of echelons. Rock solid and modern, others would say. Continuously raising the bar is your choice of approach.

You won’t be playing a follow-the-script type of a game with us. See, you are the forward-thinking, data-loving problem solver type who is seasoned to spot opportunities even when they're in stealth mode.

You’ll be joining a company where thoughtfulness, quality and focus are kept in high regard. We are passionate about not compromising on quality and choosing a long term approach to make Supercell a truly global games company that will last for many decades to come.

Time to send us your application?

Responsibilities

• Owner of Player Care specific data pipelines and data products.
• Maintain, plan and execute roadmaps for data engineering improvement in your team, as well as integrating company wide data engineering initiatives.
• Build/improve new dataset & applications upon the discovery of new insights
• Support the team in their quest to become data driven
• Define what data is collected to best serve our business needs
• Proactively suggest and implement improvements that increase scalability, robustness and availability of data systems
• Together with analytics engineering team, contribute to developing the company wide vision and strategy for data engineering practices

Requirements

• +5 years of experience in data engineering or another relevant domain
• Expert knowledge of Python and SQL
• Highly proactive and independent doer
• Strong communication skills
• Track record of maintaining large scale ETL processes
• Experience with modern data stack
• Familiarity with large scale data warehouse technologies (e.g. Databricks, Spark)
• Familiarity of build, deployment and orchestration tools
• Passion for pumping out the highest quality data in a fast-paced environment