Data Engineer at Glu Mobile (acquired by Electronic Arts in April 2021) (San Francisco, CA or Remote)

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Glu Mobile is now part of the Electronic Arts family. The combination of our talented teams at Glu and EA position us as a leader in the largest gaming category in the world. We are forming a powerful growth engine that will expand our current games and deliver more amazing new experiences across sports, lifestyle, mid-core, and casual for players everywhere. Come join us!
The Data Engineering team at Glu builds core data infrastructure and applications in support of all areas of our business, including our studio teams, analytics, user acquisition, monetization, and finance. Glu is passionate about maximizing the value that data and analytics can provide to the business and is aggressively investing in new capabilities. Our team covers a lot of ground from real-time data ingestion through to scalable data pipelines.
As a Senior Engineer, you should have a strong engineering background and have built robust data platforms and pipelines, and take complete ownership of your area of expertise. This is a fantastic opportunity to use your engineering skills to make a material impact on a highly valued analytics platform and lead the team with best engineering practices.
  • Taking ownership of and developing critical new features for our next-generation analytics platform, supporting Glu's worldwide studios and central functions such as marketing and finance
  • Building scalable, accurate, and extensible stream processing applications using cutting-edge technology such as Spark Streaming and Apache Flink
  • Implementing complex and highly scalable end-to-end data pipelines, using Elastic Beanstalk, Kinesis, EMR, Spark, Hive, Druid, Snowflake, AirflowEnsure best practices and standards in our data ecosystem are shared across teams
  • Bachelor's degree in computer science/statistics/mathematics, data engineering, or other fields with equivalent proven engineering experience
  • 5+ years of data engineering experience, especially working on back-end data infrastructure
  • Proficiency with at least one of the following languages: Java, Python, Scala
  • Experience with distributed batch and stream processing technologies such as Flink, Spark SQL, Spark Streaming, and/or Kafka Streams
  • Experience with AWS Ecosystem, especially Kinesis, EMR, Lambda, and GlueExperience with CI/CD process, testing framework, and containerization technology
  • Experience with workflow orchestration tools such as Oozie, Luigi, and AirflowKnowledge of NoSQL application data stores i.e. Druid, HBase, Cassandra, DynamoDB, Redis
  • Expertise with high-scale machine learning, i.e. Spark M/L, SageMaker, etc
  • Experience with SQL and SQL-like languages, especially Snowflake
  • Expertise building data-rich web applications, especially with technologies like Angular, js , and Elastic Beanstalk
  • Passionate about continuously adding automation process and optimization of data infrastructure
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