About the role and why it’s unique:
- As a Senior Data Infrastructure Engineer on the Infrastructure Engineering team, you’ll be building infrastructure solutions to accelerate the development of Underdog’s data systems and its workflows
- Design, build, and maintain key data infrastructure systems including distributed storage, distributed compute, and data streaming infrastructure while ensuring scalability, reliability, and security
- Accelerate developer productivity by building best in class tooling, data systems, and automation workflows
- Collaborate with engineers and data scientists to understand core system requirements and translate them into scalable technical solutions
- Implement and maintain monitoring, alerting, and observability mechanisms to ensure the health and performance of the data platform and its data quality
- Design and develop ML platforming solutions to accelerate the model development lifecycle and the development of ML inference systems
- 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 7 years of experience building distributed computing and distributed data storage infrastructure on a cloud environment (e.g. AWS, GCP, Azure)
- Well versed with containerization and orchestration technologies such as Kubernetes, ECS, or Docker
- Strong familiarity data streaming frameworks such as Apache Kafka, Apache Flink, or Kinesis
- Experience working with networking in private cloud environments and enabling cross account VPC peering functionality between multiple cloud accounts
- Expert with DevOps practices such as CI/CD pipelines, and infrastructure-as-code tools (e.g. Terraform, CDK, CloudFormation)
- Advanced proficiency with Typescript, Python, or other OOP languages (at least 2)
- Excellent leadership and communication skills with ability to influence and collaborate with engineering and data science stakeholders
- Experience with building and scaling ML platforming solutions (e.g. Databricks, Sagemaker, Vertex AI) into an existing cloud environment
Even better if you have:
- Strong interest in sports
- Prior experience in the sports betting industry
- Prior experience building data or ML platforms with accelerate computing use cases
Our target starting base salary range for this position is between $150,000 and $170,000, 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
