Data Engineer

As a Data Engineer on the Data Engineering team at Underdog, you’ll focus on building robust data pipelines that empower cross-functional stakeholders including Marketing, Product, Analytics, and Data Science with reliable, actionable data. You’ll work closely with these teams to understand their data needs and deliver scalable solutions that support their top initiatives and priorities. This role blends hands-on pipeline development with shaping the future of Underdog’s evolving data platform.

• 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

• 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)
• 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
• Experience working highly regulated industries and familiarity with data privacy and compliance frameworks (e.g. GDPR, CCPA)
• Knowledge of ML concepts, with some experience in building ML platforms

Our target starting base salary range for this position is between $135,000 and $165,000, plus pre-IPO equity. Our comp range reflects the full scale of expected compensation for this role. Offers are calibrated based on experience, skills, impact, and geographies. Most new hires land in the lower half of the band, with the opportunity to advance toward the upper end over time.

• 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
• Home office stipend
• 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

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