Data Engineer
$125,000–$155,000 year
HybridWhite Plains, New York, United States
Job Summary
Own the UFL's existing data platform by reviewing, documenting, and improving pipelines built on Fivetran, dbt, and BigQuery. Monitor ETL/ELT flows moving data from ticketing, CRM, and sales sources into BigQuery, troubleshooting ingestion issues during high-volume periods. Evaluate architecture for reliability and cost, lead data mapping for upcoming CRM migrations, and extend trusted datasets through dbt modeling. Safeguard data quality via validation and deduplication while partnering with Sales, Sponsorships, and Operations to translate needs into reliable solutions. Establish in-house engineering standards for documentation, version control, and testing. Work within sprint planning and retrospectives to keep engineering work visible and prioritized.
Required Qualifications
- Bachelor's degree in Computer Science, Information Systems, or a related field
- 3–5 years of data engineering experience
- Proven ability to step into an existing data platform - reading, documenting, and improving pipelines and code you didn't originally build
- Hands-on experience with ticketing and revenue-generation platforms (e.g., Ticketmaster/Archtics)
- Strong proficiency in SQL and Python
- Hands-on experience with Google Cloud Platform, especially BigQuery
- Working proficiency with dbt for transformation and modeling
- Experience with a managed ingestion tool such as Fivetran
- Experience with version control and collaborative development workflows (Git / Bitbucket)
- Strong data-quality instincts - validation, testing, deduplication and the judgment to make sound architecture decisions independently
- Excellent communication skills, with the ability to translate technical concepts for non-technical partners across the business
- Ability to work a flexible schedule inclusive of weekends, nights and holidays
Desired Qualifications
- Experience owning or supporting a CRM data migration (e.g., Salesforce, HubSpot), including reverse-ETL and downstream reporting impacts
- Familiarity with reverse-ETL / operational analytics patterns (e.g., Salesforce Data Cloud) and BI tools such as Looker
- Experience with digital-media and advertising data sources (e.g., Google Ads, Google Analytics, Meta)
- Prior experience with sales-intelligence tooling (e.g., ZoomInfo, LinkedIn Sales Navigator) feeding a CRM
- Comfort operating as an early or founding data hire in a fast-moving environment, with the self-sufficiency to own a domain end to end
- familiarity with Cloud Run, Cloud Storage, and Cloud Scheduler
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