EA SPORTS is one of the most iconic brands in entertainment with over 25 years of innovation, passion, and connection of millions of players across the globe to their favorite sports, teams, and players. At the heart of EA SPORTS is the FIFA franchise. EA SPORTS FIFA 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 team-work is at the heart of everything we do. With studios in Vancouver, Bucharest, and Cologne; we are looking for the brightest talent so we can continue to create experiences that connect with millions of hearts and minds the world over. Join us for the opportunity to create groundbreaking games with some of the best developer talent in the industry.

Responsibilities:

• You will work with raw data, design schemas, improve data transformation, and manage deployments and maintenance of data pipelines
• You will develop business intelligence and reporting solutions
• You will 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 partners

Required Experience

• Hands-on experience with SQL and no-SQL databases
• 1+ years of experience with Big Data technologies such as Presto, Hadoop, Spark, Databricks, Kafka, Kinesis
• 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
• Think and solve complex data engineering problems in maintainable and scalable fashion
• Experience with several programming languages such as Python, C#, Scala
• Familiarity with machine learning, and statistical approaches to data analysis

Preferred Experience

• Experience working with AWS big data technologies such as Redshift, S3, EMR, AWS Glue
• Experience with ML frameworks such as Tensorflow, PyTorch, Spark MLlib, XGBoost, and Scikit-Learn