Are you excited about handling petabytes of data and maintaining a large scalable data warehouse and compute infrastructure? Then let’s talk!

Data that we collect about our players often takes the central role in areas varying from game design to marketing to machine learning products. Our data engineers therefore take great care in keeping the data correct, up to date and easily accessible. In this position you will be responsible for ensuring that our data infrastructure is rock solid and follows modern best practices. You will be actively contributing to all data engineering areas and solving unique challenges arising from the massive scale, such as scaling Spark on Kubernetes cluster to support multiple concurrent heavy jobs.

For this role we in particular value strong devops experience and mindset. We are aiming to strengthen our team with new virtualization, clustering, containerization and automated testing skills. We also expect you to proactively advance our tech stack and drive improvement discussions.

Responsibilities

• Own and improve the infrastructure for data collection, storage and processing
• Proactively suggest and implement improvements that increase scalability, robustness and availability of data systems
• Maintain batch and real-time data pipelines
• Improve tooling used by data engineers and data scientists to manipulate and access data
• Help data scientists with ad hoc requests related to data validity and semantics
• Work closely with game teams to define what data is collected from our games
• Together with the rest of the team, develop vision and strategy for data engineering practices

Requirements

• 5+ years of experience in designing, developing and maintaining data infrastructure
• Expert knowledge of Python and SQL
• Strong devops oriented mindset
• Track record of maintaining large scale ETL processes
• Experience with AWS data stack (Kinesis, Athena+S3+Glue, RedShift)
• Hands on experience with containerization (Docker, Kubernetes, AWS EKS)
• Familiarity with large scale data warehouse technologies (BigQuery, Spark, Spark Streaming)
• Knowledge of build, deployment and orchestration tools (Azkaban or Airflow, Jenkins, Terraform)
• Ability to innovate and work independently

Nice-to-haves

• Background in backend software engineering
• Experience with GCP data stack
• Knowledge of Java and other programming languages
• Familiarity with BI tools (Periscope, Looker, Qlik Sense, Tableau)
• Experience with monitoring systems (Prometheus, Grafana)