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.

SeatGeek is a technology innovator on a mission to disrupt the $300 billion ticketing industry. We have the product, vision, and team to make life better for performers, venues, and fans, and build a generational consumer brand in the process. All we’re missing is you.

We are looking for a Software Engineer who is obsessed with solving complex data problems and is excited by the idea of expanding SeatGeek’s ecosystem of data tooling,  helping teams generate business value through data products.

What you’ll do

• Ship code to production many times a day across dozens of services
• Build a new stream ingestion process to efficiently send and store currently live listings as users see them
• Build and maintain our streaming data pipelines
• Create tooling and services that support our machine-learning applications and data products
• Evaluate new technologies and improve our software stack to keep our technological edge
• Communicate and collaborate with different stakeholders, like Data Scientists, Analysts, Software Engineers, and our Product team to produce requirements and detailed designs

What you have

• Experience building business-critical software in a fast-paced environment. We’ll be interested in hearing about what you’ve built and how
• Experience solving complex technical challenges. SeatGeek engineers create custom solutions to unique ticketing problems, including venue mapping, inventory tracking, and event matching. We’ll be excited to hear about challenging problems you’ve solved
• Passion for software craftsmanship and product. You have well-considered opinions about how software should work, and hold yourself and your code to a high standard
• Commitment to your teammates. You enjoy working with a diverse group of people with different experiences and take pride in mentoring and learning from others

Our stack

You do not need experience with all of these, but we thought you might be curious. What we care about is your experience, skills, and approach to problem solving. Tools can be learned.

• Languages: Java and Python for general-purpose development
• Frameworks: Airflow, Flink, Spark on EMR clusters for distributed processing
• Stack: Docker containers running on k8s on AWS
• Streaming: Flink, Debezium, and Kafka
• Datastores: Postgres, Redshift and S3
• Other: AWS Lambda, Git, dbt, Docker

Perks: