Data Engineer

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Apache Hadoop, Scala Programming, Machine learning techniques, Data science techniques, PyTorch, TensorFlow, MapReduce, R Programming

Job Description

SeatGeek believes live events are powerful experiences that unite humans. With our technological savvy and fan-first attitude we’re simplifying and modernizing the ticketing industry.

By catering to both consumers and enterprises, we’re powering a new, open entertainment ecosystem where fans have effortless access to experiences, and teams, venues, and shows have seamless access to their audiences. Because everyone should expect more from ticketing.

Data engineers are members of SeatGeek’s data platform team. As a team, we share common views on experimental rigor, pragmatism, and software quality. Data engineers focus on maintaining and expanding our ecosystem of data pipelines. These pipelines provide the basis for many crucial downstream processes: complex analyses, data products, and business performance measurement.

What you'll do

• Deploy a high-performance ML model that processes a stream of user activity to detect changes in event demand
• Build a new stream ingestion process to efficiently send and store currently live listings as users see them
• Build reporting infrastructure and integrations for our enterprise clients (pro sports teams, Broadway theaters, etc.)

Who you are

The ideal candidate can relay complex concepts to both technical and non-technical audiences, enjoys partnering with both business users and application developers, and has a proven ability to build systems that allow greater clarity, consistency, and efficiency in utilizing data. Experience with specific tools is less important than aptitude and drive, but at a minimum, we would expect:

• 3-5 years experience developing on and maintaining ETL systems, and a high level understanding of different data processing systems
• Experience working cross-functionally with different business units to translate business problems into data problems and solve them
• Comfort turning ideas into code (bonus points for experience with Python or Scala)
• Proficiency with analytical and operational SQL queries, and knowledge of how to optimize and troubleshoot

Bonus points for candidates who have experience with or desire to learn any of the following:

• Data-processing frameworks (Spark, Flink)
• Streaming data/message queues (Akka streams, Kafka)
• AWS infrastructure (we use Redshift, S3, EMR, Kinesis, Lambda, Glue, and RDS)
• Dimensional modeling, especially in e-commerce or consumer tech
• Database internals and tuning, trade-offs and benefits of different datastores (both analytical and transactional)
• Optimization of complex data workflows that reconcile batch and streaming data
• Dependency management at scale across multiple classes of data source

The tools we use

You absolutely do not need experience with all of these, but we thought you might be curious. Tools can be learned, so we care much more about your general engineering skill than knowledge of a particular language.

• Languages: Scala and Python for general purpose development
• Frameworks: Luigi for dependency management, Spark on EMR for map/reduce
• Stack: Docker containers running on Nomad on AWS
• Streaming: Flink, Akka Streaming, Kinesis (+Firehose), and Kafka
• Datastores: Postgres, MySQL and SQL Server in production, Redshift and S3
• Other: AWS Lambda, Git, dbt, Docker

Perks:

• Equity stake
• Flexible work environment, allowing you to work as many days a week in the office as you’d like or 100% remotely
• A WFH stipend to support your home office setup
• Flexible PTO
• Up to 16 weeks of paid family leave
• 401(k) matching program
• Health, vision, dental, and life insurance
• Annual subscriptions to Headspace, Ginger.io, and One Medical 
• $120 a month to spend on tickets to live events
• Annual subscription to Spotify, Apple Music, or Amazon music