Data Engineer – AAA Games company – South East, UK

Our client is a leading global interactive entertainment software company. They build and deliver games, content and online services to millions of people across the globe with the most amazing and immersive interactive software in the industry.

Your role as part of Global Analytics and Insights Technology (GAIT) will be to build last-mile global analytics and reporting solutions that depict player evolution year-over-year in some outstanding AAA titles.

You will help build a platform to process petabytes of data into pipelines for user-facing environments and collaboratively compete for the industry-leading data program – all while serving needs of teams on the cutting edge of game development using DevOps methodologies.

Responsibilities

• Maintain and enhance our core data infrastructure and ETL framework.
• Develop and maintain data sets to support reporting and exploratory analytics.
• Develop and own core tools, frameworks, and our Kubernetes-based platform.
• Assess and recommend available and emerging big data technologies.
• Contribute to post implementation reviews helping to demonstrate success.

Requirements

• Bachelor’s or Master’s degree in computer science, software engineering or similar.
• Be fluent in Python and some flavour of SQL.
• Write clean, effective, re-usable code that can be used to scale applications.
• Have experience with cloud platforms such as AWS and GCP.
• Are comfortable on the command-line and working with servers.
• Built and used CI/CD pipelines in the past – Docker experience is essential.
• Proactive to remain technically capable and an expert in current technologies.

Additional skills

• Basic knowledge of other languages such as Java, Scala and C#.
• Have actively used Kubernetes + Helm and other orchestration tools such as Apache Airflow.
• Are comfortable using infra-as-code tools such as Terraform.
• Bring a “If it can be automated, it will be automated” mentality.
• Experience with adapting purpose-built applications into cloud and on-premise platforms.
• Spent time throttling multiple systems to achieve target performance for SLAs.
• Understand the physical and logical design of cloud-native database such as Snowflake.

Tagged as: Data Analyst, Data Engineer