Anaytics Engineer
Salary
The salary range for this role is $115,000-$160,000
We are looking for an Analytics Engineer to join SeatGeek’s Data team. You will join a high-performing team that partners closely with business stakeholders for their data management and insights generation needs. Analytics Engineers play a critical role in discovering, extracting, storing, cataloging, modeling, and processing our data. As a member of this team you will extract data from production and third-party sources using Fivetran, build data models in our data warehouse, and manage our orchestration using Airflow in order to produce clean, well-documented, and analysis-friendly datasets. This is a highly collaborative role; you will own relationships with both analysts and production engineers to discover the value of our data. By putting data at the heart of everything we do, your work will drive us toward our mission of making SeatGeek the top destination for live event goers.
The live event industry continues to boom and the future is up for grabs. Operators across SeatGeek will need clean, actionable metrics and feedback loops to make company-defining decisions. If you’re somebody who has a strong opinion on how we should build and use data to fuel decision-making, you’re the right person for this role.
What you’ll do
- Join a team of Analytics Engineers that will develop data pipelines and use SQL- and Python-based ETL frameworks to acquire, process, and deliver data to consumers around SeatGeek
- Communicate and collaborate with different stakeholders, like Data Scientists, Analysts, Data Platform Engineers, and Software Engineers to understand data use cases and product requirements for R&D teams
- Implement cataloging best practices and lead the definition, collection, documentation of our data sources. Invest in end-user data literacy through hands-on training with folks around the company
- Architect and thoroughly QA performant data models that enable analysis in a data warehouse setting
- Assist in triaging and debugging on-call requests in a rotational on-call schedule with the Analytics Engineering team
What you have
- 3+ years of relevant experience in Analytics, Data, or Software Engineering
- Experience with dbt is a plus
- A bachelor’s degree or higher in economics, psychology, computer science, statistics, mathematics or another quantitative discipline
- Expert-level knowledge of SQL. Proficiency in programming with Python
- Experience developing new metrics and performing analysis with large datasets
- Experience cleaning data sets, developing new models and interfacing with stakeholders to understand business requirements
Our stack
- Scheduling/Orchestration: Airflow
- ETL: Fivetran, Python, dbt, & Kafka
- Data Warehouse: Redshift
- Event Stream: mParticle
- Experimentation: Optimizely
- Dashboarding: Looker, Hex, & Mixpanel
- Code versioning: Gitlab
- Required languages: SQL and Python