Data Engineer

XFL Properties DBA United Football League•White Plains, NY

12d•Hybrid

About The Position

The Data Engineer will play a foundational role in the UFL's data ecosystem. As the first dedicated engineering hire on the Data & Business Intelligence team, this role is responsible for owning and evolving the pipelines, warehouse, and data models that power Sales, Sponsorships, Marketing, and Football Operations. The Data Engineer will take ownership of an established modern data platform built on Fivetran, dbt, and BigQuery, leading its evolution as the league grows. This role is responsible for configuring and improving the data & insights that drive every decision and will establish the engineering practices a growing data function will depend on. The Data Engineer will partner closely with the broader Data & BI team to ensure data flows reliably across the business and to extend well-structured, trusted datasets for the organization. This foundation supports advanced analytics, reporting, and future machine learning. The role requires technical depth and sound judgment on architecture decisions, paired with the ability to translate for non-technical partners. The ideal candidate thrives in a collaborative, early-stage environment, is meticulous about data quality, and is motivated by building durable solutions that drive real business value.

Requirements

Bachelor's degree in Computer Science, Information Systems, or a related field. An equivalent combination of education and hands-on experience may be considered.
3–5 years of data engineering experience, including ownership of production pipelines that other teams or systems depend on.
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) and the data they produce, ideally within a sports, entertainment, or live-events organization.
Strong proficiency in SQL and Python, with experience developing, maintaining, and extending production data pipelines.
Hands-on experience with Google Cloud Platform, especially BigQuery (familiarity with Cloud Run, Cloud Storage, and Cloud Scheduler a plus).
Working proficiency with dbt for transformation and modeling, and 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.

Nice To Haves

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.

Responsibilities

Take ownership of the UFL's existing data platform. Review, understand, and support the current pipelines and warehouse (Fivetran, dbt, BigQuery, Cloud Run) originally stood up with an external partner, and serve as the in-house owner accountable for their reliability and evolution.
Operate and maintain core data flows. Monitor the ETL/ELT and reverse-ETL pipelines that move data from source systems (ticketing, digital media, CRM, sales intelligence) into BigQuery and back out to operational tools, troubleshooting ingestion, transformation, and delivery issues, including during high-volume periods of the season.
Evaluate existing architecture, identify gaps and opportunities, and drive adjustments that improve reliability, cost, and performance as the league's needs grow.
Own the data side of platform migrations. Lead data mapping, movement, and validation for source-system changes, including an upcoming CRM migration that touches ingestion, reverse ETL, and reporting.
Extend trusted, well-modeled datasets. Build on and maintain the dbt models in BigQuery that serve as the single source of truth the analytics and CRM functions rely on.
Safeguard data quality. Maintain accuracy and trust through validation, deduplication, and classification.
Partner with Sales, Sponsorships, Marketing, Finance and Football Operations to translate needs into reliable data solutions.
Establish in-house data engineering standards. As the first internal data engineer, define the documentation, version-control, and testing practices needed to bring the platform fully in-house and scale it.
Work within the team’s development practices (standups, backlog grooming, sprint planning and retrospectives) and set the standard for the engineering voice in the room, keeping engineering work visible, scoped and prioritized alongside analytics and CRM.