Electronic Arts - Data Engineer

• Ability to think and solve complex data engineering problems in maintainable and scalable fashion
• Hands-on experience with SQL and no-SQL databases
• 1+ years of experience with Big Data technologies such as Trino, Spark, Databricks, Kafka
• 1+ years of experience with data pipeline and workflow management tools such as Airflow
• 1+ years of experience using business intelligence reporting tools such as Tableau or Looker
• 1+ years of experience working with Cloud technologies (preferably AWS)
• Knowledge and experience with several programming languages such as Python, C#, Scala
• Familiarity with machine learning, and statistical approaches to data analysis

We are a global team of creators, storytellers, technologists, experience originators, innovators and so much more. We believe amazing games and experiences start with teams as diverse as the players and communities we serve. At Electronic Arts, the only limit is your imagination.

EA SPORTS is one of the most iconic brands in entertainment – connecting hundreds of millions around the world to the sports they love through a portfolio of industry-leading video games.

At the heart of EA SPORTS is the FC franchise. EA SPORTS FC is the world's #1 best-selling video game with over 200M engaged players across multiple platforms, including console, PC, and mobile. Innovation, passion, and teamwork are at the heart of everything we do. With studios in Vancouver, Bucharest, and Cologne, we're looking for the brightest talent, so we can continue to create experiences that connect with millions of hearts and minds the world over.

Reporting to the Data Science Manager, we are looking for a Data Engineer passionate about building high impact end to end data pipelines driving actionable insights. We are a small team of multidisciplinary data professionals. The ideal candidate is comfortable working in a dynamic environment where they can wear multiple hats to achieve the business goals while delivering quality work. Daily responsibilities include but are not limited to working directly with stakeholders to collect requirements, write design documents, implement ETLs and data quality checks.

Your Responsibilities:

• Work with raw data, design schemas, optimize data transformation, and manage deployments and maintenance of data pipelines
• Develop business intelligence and reporting solutions
• Develop real-time ingestion, processing, and alerting data pipelines
• Evaluate feasibility and effectiveness of proposed data solutions
• End-to-end administration and maintain tools, systems, pipelines and ETLs
• Communicate designs, issues, and trade-offs to stakeholders