Data Engineer

Alpha Opco LLC

$125K — $155K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Computer Science, Information Systems, or related field; equivalent experience considered.
  • 3-5 years of data engineering experience with production pipeline ownership.
  • Ability to analyze and improve existing data platforms and pipelines.
  • Hands-on experience with ticketing systems (e.g., Ticketmaster) in sports or live events.
  • Strong SQL and Python skills with production data pipeline experience.
  • Experience with Google Cloud Platform, particularly BigQuery.
  • Proficiency with dbt for data modeling and Fivetran for ingestion.

Responsibilities

  • Own the existing data platform and ensure its reliability and evolution.
  • Maintain core data flows and monitor ETL/ELT pipelines for issues.
  • Evaluate and improve data architecture for reliability and performance.
  • Lead data mapping and validation for platform migrations.
  • Build and maintain well-modeled datasets for analytics and CRM functions.
  • Safeguard data quality through validation and deduplication processes.
  • Establish data engineering standards and practices for in-house operations.

Benefits

  • Medical, dental, and vision insurance coverage.
  • 401(k) plan with employer contribution.
  • Unlimited paid time off (PTO).
  • Eligibility for annual bonus incentives.
Full Job Description
Position: Data Engineer

Reports to: VP, Data & Business Intelligence

Location: White Plains, NY (Hybrid)

ABOUT THE ROLE

The Data Engineer will play a foundational role in the UFL's data ecosystem. The first dedicated engineering hire on the Data & Business Intelligence team, responsible for owning and evolving the pipelines, warehouse, and data models that power Sales, Sponsorships, Marketing, and Football Operations.

As our first in-house engineer, you'll take ownership of an established modern data platform built on Fivetran, dbt, and BigQuery, while leading its evolution as the league grows. You'll be responsible for configuring and improving the data & insights that drive every decision. The Data Engineer will establish the engineering practices a growing data function will depend on. You'll partner closely with the broader Data & BI team to keep data flowing reliably across the business and to extend the well-structured, trusted datasets the whole organization works from. This foundation is the groundwork for advanced analytics, reporting, and future machine learning.

This role requires technical depth and sound judgment on architecture decisions, paired with the ability to translate for non-technical partners across the business. 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.

WHAT YOU WILL DO
  • 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


WHAT YOU WILL BRING
  • 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


PREFERRED 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


OTHER DUTIES

Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice.

ADDITIONAL DETAILS
  • The role is hybrid, works in a remote office and/or an office environment and will be expected to attend all games and events.
  • Position may require periods of sitting at a desk, frequent bending, moving, lifting, and carrying material weighing up to 20 pounds.
  • Minimal Travel (
  • Ability to work a flexible schedule inclusive of weekends, nights and holidays required
  • Other duties as assigned by VP, Data & Business Intelligence

COMPENSATION

The salary range for this position is $125,000 - $155,000. This role is eligible for annual incentive and/or comprehensive benefits, including medical/dental/vision/life insurance, a 401(k) plan, unlimited PTO and offers a discretionary bonus. The actual base salary offered will depend on a variety of factors, including, without limitation, the qualifications of the individual applicant for the position, years of relevant experience, level of education attained, certifications or other professional licenses held, and if applicable, the location of the position.

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