Senior Data Analyst, Supply
SeatGeek USAUSD 108,000–157,000 / yearSenior
Key requirements
- Python
- Sql
- Airflow
- Dbt
- Data Science
- Looker
SeatGeek believes live events are powerful experiences that unite humans. With our technological savvy and fan-first attitude we’re simplifying and modernizing the ticketing industry.
We're looking for a Senior Data Analyst to join our Analytics team and focus on the supply side of SeatGeek's marketplace. You'll partner with stakeholders across the Supply organization, with extra focus on our seller and client-facing teams. Using advanced analytics, you'll turn raw data into insights that shape decisions, surface opportunities, and drive measurable results.
This is a high-impact individual contributor role for someone who thrives on ambiguity, knows how to connect business strategy to marketplace and product data, and has a passion for identifying the most meaningful opportunities to improve user and business outcomes. As a member of SeatGeek’s Analytics team, you will be able to collaborate with and learn from a group of high-performing analysts, data scientists, and engineers.
What you'll do
Develop a deep understanding of the live events business and how supply dynamics drive marketplace health
Partner with stakeholders on the Supply, Product, and Engineering teams, understanding their objectives and defining an analytics roadmap to support those goals
Guide seller policy decisions — such as fees, fulfillment standards, and seller performance requirements — by quantifying trade-offs up front and measuring impact after launch
Work directly with the Client Success and Entertainment teams that manage our relationships with sports teams and venues, identifying opportunities to maximize the value of our partnerships and help our clients grow their businesses
Equip account managers with data-driven insights to strengthen seller relationships and uncover growth opportunities
Leverage first-class AI dev tools to build out measurement frameworks, develop key reporting, and collaborate with engineers to drive rapid iteration of features, bringing ideas to life faster than ever before
Conduct exploratory and root-cause analysis to explain shifts in performance and surface pockets of opportunity for improvement
Translate complex analysis into clear, data-driven narratives and recommendations for internal leaders
Create or improve key datasets and contribute to our analytical tooling ecosystem (e.g. dbt, Hex) to ensure we can answer today’s questions and tomorrow’s
What you have
4+ years of experience working in analytics, data science, or adjacent roles — preferably in tech, ecommerce marketplaces, or consumer products
Expert-level knowledge of SQL and experience performing analysis with large datasets
Demonstrated ability to own ambiguous problem spaces, from framing questions to delivering recommendations
Strong communication skills — able to simplify complex analyses, defend methodology choices, and inspire action through insights
Excited to contribute to a team culture centered around curiosity, humility, and impact
A track record of influencing business strategy with data
Nice-to-have: Domain expertise or past experience with a two sided marketplace
Our stack
You absolutely do not need experience with all of these, but we thought you might be curious. Tools can be learned, so we care much more about your general engineering skill than knowledge of a particular language.
Required languages: SQL (Python nice-to-have)
Data Warehouse: Redshift
Dashboarding: Looker & Hex
Version control: GitLab
AI tooling: Claude Code, Hex Agent
Scheduling/Orchestration: Airflow
ETL: Fivetran, Python and dbt
Event Stream: mParticle
Experimentation: Eppo
Product Analytics: Mixpanel
Perks
Equity stake
Discretionary annual bonus
Flexible work environment, allowing you to work as many days a week in the office as you’d like or 100% remotely
A WFH stipend to support your home office setup
Unlimited PTO
Up to 16 weeks of fully-paid family leave
401(k) matching
See your match score for this role.
Xecodai maps the interview stages and shows what is preventing a 95% match.
