About Metica

Metica is an AI-based growth technology platform designed specifically for games. We empower gaming studios and publishers to drive player installs, engagement, and monetization through advanced personalization, optimization, and machine learning technologies. By unifying growth strategies across user acquisition, in-app purchases, subscriptions, and player experiences, Metica helps gaming companies achieve their full potential.

The Role

We’re looking for a skilled Data Engineer to join our team and help us build and scale the data infrastructure that powers Metica’s cutting-edge personalization and optimization solutions. In this role, you’ll design and implement robust data platforms, pipelines, and systems that process and analyze vast amounts of data in real-time. Your work will directly impact our ability to deliver game-changing insights and tools to some of the world’s leading gaming studios and publishers.

This is an exciting opportunity for a hands-on data engineer who thrives in a startup environment, loves solving complex problems, and is passionate about gaming and data-driven technology. This is an in-office role based in London, with the flexibility to work from home one day per week.

You Will

• Design, build, and maintain scalable data pipelines using tools like Spark, Dask, Pandas, or Ray.
• Develop data platforms such as data lakehouses, data lakes, and data warehouses.
• Work with big data platforms like EMR, Databricks, or DataProc to process and manage large datasets.
• Leverage your expertise in cloud environments (AWS, Azure, or Google Cloud) to ensure the scalability and reliability of our systems.
• Support and operate production systems, ensuring data pipelines run smoothly and efficiently.
• Collaborate with product, engineering, and data science teams to optimize platform performance and functionality.

You Need

• Demonstrable experience building data pipelines with Spark, Dask, Pandas, or Ray.
• Proficiency in programming languages such as Python (preferred), Scala (preferred), and Java (desirable).
• Hands-on experience working with cloud providers like AWS, Azure, or Google Cloud.
• Proven knowledge of big data platforms like EMR, Databricks, or DataProc.
• Expertise in building and managing data platforms, including data lakehouses, lakes, or warehouses.
• Bonus points for experience in any of the following areas: automated data quality frameworks, CI/CD pipelines, machine learning models, Infrastructure as Code tools or data visualization tools