Underdog is looking to build robust data pipelines to empower cross-functional stakeholders with reliable, actionable data and shape the future of their evolving data platform.
Requirements
- 3+ years of experience building scalable data pipelines in a cloud-native environment (AWS, GCP, or Azure)
- 2+ years of experience using dbt, Flink, or Spark for data transformations and BI tools such as Sigma or Looker
- Advanced proficiency with Python and SQL
- Some experience with streaming data infrastructure such as Apache Kafka, Apache Flink, GCP Datastream or AWS Kinesis
- Some familiarity with DevOps practices such as CI/CD pipelines, and infrastructure-as-code tools (e.g. Terraform, CDK)
- Knowledge of ML concepts, with some experience in building ML platforms
Responsibilities
- You’ll be developing data pipelines and maintaining production quality datasets that support Underdog’s analytics, data science, and marketing teams
- Design, build, and optimize scalable data platform infrastructure to support batch and real-time data processing and storage in the cloud
- Collaborate with analytics, data scientists, engineers, and other business stakeholders to understand data requirements and translate them into scalable technical solutions
- Implement and maintain monitoring, alerting, and logging mechanisms to ensure the health and performance of the pipelines and platforms
- Perform validation and build data quality checks on production datasets and ensure there are minimal data quality issues
- Communicate continuously about progress, blockers, and resolution steps to all relevant stakeholders
Other
- Strong ownership mindset; you’re focused on delivering results in a fast-paced, entrepreneurial environment
- A proactive problem solver who finds and implements opportunities to improve systems and processes
- Excellent communication skills, with the ability to influence and collaborate effectively across teams
- Strong interest in sports
- Prior experience in the sports betting industry
