Data Engineer – Hybrid: Own a Modern Data Platform

UFL; City of White Plains (NY); Hybrid; USD 125.000 - 155.000; Vollzeit

Benefits dieser Stelle

Medical/dental/vision insurance

401(k) plan

Unlimited PTO

Performance bonus

Zusammenfassung

UFL is seeking a Data Engineer in White Plains, NY (Hybrid preferred or Open to Remote) to own and evolve its data platform. You will work on pipelines, warehouse, and data models powering Sales, Sponsorships, Marketing, and Football Operations.

The role requires building durable, trusted datasets and partnering with business teams to translate needs into reliable data solutions. You will set in-house engineering standards and contribute to analytics and future ML initiatives.

Qualifikationen

• Bachelor's degree in CS, IS, or related field.
• 3–5 years of data engineering experience.
• Experience owning production data pipelines and platforms.

Aufgaben

• Take ownership of the UFL's existing data platform and ensure reliability and evolution.
• Operate and maintain core data flows.
• Monitor ETL/ELT and reverse-ETL pipelines into BigQuery and back to ops tools.
• Evaluate architecture gaps and improve reliability, cost, and performance.
• Lead data mapping and validation for source-system changes, incl. CRM migration.
• Extend dbt models in BigQuery as the single source of truth.
• Establish data engineering standards and practices in-house.
• Collaborate with Sales, Sponsorships, Marketing, Finance and Football Operations.

Kenntnisse

SQL

Python

BigQuery

dbt

Fivetran

Looker

Git/Bitbucket

Cloud Run

Ausbildung

Bachelor's degree in Computer Science, Information Systems, or related field

Tools

dbt

BigQuery

Fivetran

Looker

Git

Python

SQL

Jobbeschreibung

UFL is seeking a Data Engineer in White Plains, NY (Hybrid preferred or Open to Remote) to own and evolve its data platform. You will work on pipelines, warehouse, and data models powering Sales, Sponsorships, Marketing, and Football Operations.

The role requires building durable, trusted datasets and partnering with business teams to translate needs into reliable data solutions. You will set in-house engineering standards and contribute to analytics and future ML initiatives.