Job Overview
Job TitleAnalytics Engineer
Job TypeFull Time
Offered Salary$150,000
LocationNew York, NY
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Job Description
About SeatGeek
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.Job Summary
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 own our analytics data layer. You’ll work on extracting data from production databases as well as third party sources, architecting efficient data models, and orchestrating jobs in Airflow 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.
- 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.
- Enable AI-assisted stakeholder data analysis by designing LLM-friendly DWH schemas, creating domain guides, and enforcing canonical naming conventions across all tables to be consumed by the AI agent.
- Partner with Analytics leadership to develop a strategy around BI tooling to ensure stakeholders have easy access to usable data.
What You Have
- 2+ years of relevant experience in Analytics, Data, or Software Engineering.
- Experience with DBT, databricks, or similar SQL-transformation tool is a must.
- 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.
- Expert verbal and written communication skills. You are able to translate complex problems or concepts into clear frameworks and guides that all audience types can understand.
Our Stack
- Scheduling/Orchestration: Airflow
- ETL: Fivetran, Python, dbt, & Kafka
- Data Warehouse: Redshift
- Event Stream: mParticle
- Experimentation: Eppo
- BI: Looker, Hex, & Mixpanel
- Code versioning: Gitlab
- Required languages: SQL and Python
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
- Eligible for the SG discretionary annual bonus based on individual and company performance
- Up to 16 weeks of fully-paid family leave
- 401(k) matching
- Student loan matching program
- Health, vision, dental, and life insurance
- Up to $25k towards family building, reproductive health services and Gender-affirming care
- $500 per year for wellness expenses
- Subscriptions to Headspace (meditation), Headspace Care (therapy), and One Medical
- $120 per month to spend on tickets to live events
- Annual subscription to Spotify, Apple Music, or Amazon music
Key skills/competency
- Analytics Engineering
- SQL
- Python
- Data Modeling
- ETL
- Data Warehousing
- Airflow
- DBT
- Data Pipelines
- Stakeholder Management
How to Get Hired at SeatGeek
- Tailor your resume: Highlight your 2+ years of experience in Analytics Engineering, specifically mentioning DBT, databricks, SQL, and Python proficiency.
- Showcase your skills: Quantify your achievements in data modeling, ETL processes, and stakeholder communication.
- Prepare for technical interviews: Brush up on advanced SQL, Python for data manipulation, and data warehousing concepts.
- Understand SeatGeek's mission: Research their role in modernizing the ticketing industry and how data drives their success.
- Network and inquire: Connect with current employees on LinkedIn for insights into the team culture and interview process.
Frequently Asked Questions
Find answers to common questions about this job opportunity
01What is the typical career path for an Analytics Engineer at SeatGeek?
02How does SeatGeek support AI and LLM integration in analytics?
03What is the on-call rotation like for the Analytics Engineering team at SeatGeek?
04Can I work remotely as an Analytics Engineer at SeatGeek?
05What kind of data analysis and modeling experience is most valued for this Analytics Engineer role at SeatGeek?
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