United States onlyAt Underdog, we make sports more fun.
Our thesis is simple: build the best products and we’ll build the biggest company in the space, because there’s so much more to be built for sports fans. We’re just over five years in, and we’re one of the fastest-growing sports companies ever, most recently valued at $1.3B. And it’s still the early days.
We’ve built and scaled multiple games and products across fantasy sports, sports betting, and prediction markets, all united in one seamless, simple, easy to use, intuitive and fun app.
Underdog isn’t for everyone. One of our core values is give a sh*t. The people who win here are the ones who care, push, and perform. If that’s you, come join us.
Winning as an Underdog is more fun.
At Underdog, data isn’t just an asset — it’s a competitive advantage. As our first Analytics Engineering Manager, you’ll lead the function that turns raw data into the foundation for insights, metrics, and decision-making. This is a unique opportunity to shape a nascent team, establish best practices, and build the semantic layer and models that power analytics across the business. You’ll be both a technical contributor and a leader, ensuring that Underdog’s data is reliable, consistent, and a true driver of growth.
About the role
- Define and execute the Analytics Engineering team charter and roadmap, clarifying scope, ownership, and priorities.
- Lead, mentor, and grow a team of Analytics Engineers, fostering a culture of technical excellence and business impact.
- Personally contribute (as a “player-coach”) to high-impact dbt models and pipelines, setting the standard for code quality and best practices.
- Stand up and operationalize a semantic layer (dbt MetricFlow, Omni, or equivalent) as the single source of truth for company metrics.
- Implement engineering rigor in analytics workflows: version control, CI/CD, testing frameworks, and observability.
- Partner with Data Engineering, Analytics, and Data Science to ensure seamless handoffs from ingestion to analysis.
- Deliver early business-critical wins (e.g., Finance-ready revenue model, Marketing attribution pipeline) that demonstrate AE’s impact.
- Build trust and alignment across stakeholders with clear communication, documentation, and recurring forums.
Who you are
- Experienced data leader with 7+ years in analytics engineering, BI, or data engineering, including 2+ years mentoring or managing teams.
- SQL and dbt expert, fluent in modern data modeling patterns and cloud warehouses (Snowflake, BigQuery, Databricks).
- Skilled in workflow orchestration (Airflow, Dagster, Prefect), Git-based workflows, and CI/CD in data.
- Strong understanding of semantic layers and their role in enabling consistent, scalable self-service analytics.
- Effective communicator who builds trust across technical and business stakeholders.
- Bias for action — thrives in a fast-paced startup environment and enjoys solving ambiguous problems.
Even better if you have
- Experience building or scaling an Analytics Engineering team from scratch.
- Exposure to sports, fantasy sports, or gaming data.
- Familiarity with real-time or streaming architectures.
- Hands-on experience with data observability tools (Monte Carlo, Elementary).
- Contributions to the analytics engineering community (open-source, blogs, talks).
Our target starting base salary range for this position is between $215,000 and $240,000, 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
- 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
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.
