Sr Software Eng (Baseball Data)
MLB Advanced Media
San Francisco, California, United States
Job type: fulltime
Job industry: Community & Sport
Reports To: Associate Director, Engineering
Location: San Francisco, CA
MLB Advanced Media is looking for experienced Software Engineers that are passionate about building new technologies for the baseball industry. Launched in 2001 as the tech arm of Major League Baseball, MLBAM is now a leading authority in real-time sports data processing, distribution and analysis.
The Baseball Data team is the central data hub for MLB. Using cutting edge technology, our data is consumed by fans, broadcasters, stadiums, and MLB teams. Our team's primary product line is MLB.com Gameday, Statcast and Pitchcast. You can find more information about Statcast at
As a Senior Software Engineer, your primary Responsibilities will be to write clean, concise, modular code in an agile environment, mentor developers and provide code reviews.
- Lead and take ownership of critical projects and your own initiatives.
- Introduce the technologies you feel passionate about.
- Collaborate with a team of extraordinary engineers and technologists.
- Influence the innovation of products used by millions of users worldwide.
- Work alongside top data scientists on data analysis, machine vision and NLP.
- Participate in the full lifecycle of software development (Requirements gathering, designing, building, testing and maintenance).
- Change the way baseball is consumed.
- Receive amazing benefits - you get 100% employer-paid Medical, Dental and Vision.
- 5+ years of experience using JVM languages (Java, Scala, Kotlin…).
- Experienced building large and scalable applications.
- An avid learner, independent with excellent problem-solving skills.
- Passionate about mentoring peer developers, providing code reviews, etc.
- Baseball fan.
Preferred, but not required:
- Exposure to Amazon Web Services.
- Familiar with messaging queues: ActiveMQ, Kafka, Kinesis and SNS/SQS.
- Experience with SQL databases
- Understanding of big data concepts and knowledge of big data languages/tools such as Hive, Pig, Mahout or Spark
- Experience with 3D modeling and statistical analysis of 3D models
- Can explain the difference between FIP and ERA to the creator of FIP.