Data Engineer

Hi, we’re Underdog!

We’re the fastest-growing sports gaming company ever.

We build innovative games and products for American sports fans.

Founded in 2020, our team built four of today’s most widely played fantasy games and recently launched our Underdog Sportsbook. We are the only sportsbook to ever launch on our own home grown technology, which allows us to build different and innovative experiences. We believe there’s so much more to be built for sports fans, and we’ll continue to win by building the best products and experiences for our customers.

The opportunity in front of us to become the biggest company in our space is massive; after all, we’re currently sitting in the fastest-growing consumer industry in the U.S. In just over two years, we reached a nearly $500 million valuation through some of the best investors in the game, including Mark Cuban, Kevin Durant, BlackRock, and SV Angel. We are many times larger now and our growth is not slowing down.

At Underdog, we believe that sports are for everyone and are building a tomorrow for every fan. Want to help create that future? Join us.

About the role and why it’s unique:

• As a Data Engineer on the Data Platform team, you’ll be architecting and developing Underdog’s sports focused data systems and data pipelines
• Design, build, and optimize scalable data platform infrastructure using Terraform to support batch and real-time data processing and storage on the cloud using Kafka, Kinesis, RDS, and S3
• Implement and maintain monitoring, alerting, and logging mechanisms to ensure the health and performance of the data platform
• Collaborate with data scientists, engineers, and business stakeholders to understand data requirements and translate them into scalable technical solutions
• Lead code reviews, provide constructive feedback, and evangelize best practices to maintain code and data quality
• Research and keep up to date on emerging data technologies and trends and focus on iteratively implementing them into Underdog’s data systems

Who you are:

• At least 3 years of experience building scalable and durable data pipelines and data systems on a cloud environment (e.g. AWS, GCP, Azure)
• Highly focused on delivering results for internal and external stakeholders in a fast-paced, entrepreneurial environment
• Excellent leadership and communication skills with ability to influence and collaborate with stakeholders
• Strong familiarity with distributed computing and data storage mechanisms on the cloud environment with hands-on experience in managing data infrastructure
• Familiarity with containerization and orchestration technologies such as Docker, Kubernetes, or ECS
• Experience with data streaming frameworks such as Apache Kafka, Apache Flink, or Kinesis
• Advanced proficiency with Python and SQL
• At least one year of experience with Golang
• Experience with DevOps practices such as CI/CD pipelines, and infrastructure-as-code tools (e.g. Terraform, CDK, CloudFormation)

Even better if you have:

• Strong interest in sports
• Prior experience in the sports betting industry
• Knowledge of ML concepts, with some experience in building inference systems

Our target starting base salary range for this position is between $135,000 and $150,000, plus target equity. The starting base salary will depend on a number of factors including the candidate’s skills and experience, among other things.

What we can offer you:

• Unlimited PTO (we're extremely flexible with the exception of the first few weeks before & into the NFL season)
• 16 weeks of fully paid parental leave
• A $500 home office allowance
• A connected virtual first culture with a highly engaged distributed workforce
• 5% 401k match, FSA, company paid health, dental, vision plan options for employees and dependents

#LI-REMOTE

This position may require sports betting licensure based on certain state regulations.

Underdog is an equal opportunity employer and doesn't discriminate on the basis of creed, race, sexual orientation, gender, age, disability status, or any other defining characteristic.