Data Engineer

This onsite Data Engineer role on Major League Baseball’s LAI team focuses on building and operating production data pipelines within a GCP lakehouse, leveraging Airflow and dbt to empower analytics across the league. The position is based in New York, NY.

Responsibilities

• Develop production-grade pipelines with Airflow and dbt to orchestrate batch and streaming transformations across GCP, ensuring downstream analysts and engineers can rely on accurate data without tracing wiring issues.
• Design clean, layered data models (staging, intermediate, and mart) that serve as the single source of truth for league analytics, applying dbt practices for materialization, testing, and documentation.
• Manage the ingestion layer with Pub/Sub, GCS, Dataflow, and Knowledge Catalog DataPlex to land both batch and streaming sources into the lakehouse in a clean, reliable manner.
• Establish observability and monitoring standards to surface data quality issues before stakeholders notice them.
• Maintain code via GitHub-based CI/CD, contributing to deployment workflows that keep the platform reliable and changes safe.
• Follow data governance practices to safeguard proprietary baseball data and ensure compliance.

Requirements

• 2–4 years of production data engineering experience.
• Expert-level SQL with the ability to craft complex queries and interpret others' code to identify issues.
• Strong Python skills for data processing, scripting, and automation.
• Hands-on dbt experience across staging, intermediate, and mart layers, with tests and production deployment.
• Production Airflow experience including DAG authoring, dependency management, and debugging failed runs.
• Deep familiarity with Google Cloud Platform (BigQuery, GCS, Pub/Sub) or equivalent depth in AWS/Azure with willingness to convert.
• Git-based development workflows, including branches, PRs, and code reviews as part of daily practice.
• Clear communication with both engineers and non-technical stakeholders, receptive to feedback and collaborative in approach.
• Execution mindset with the ability to own a project from requirements through deployment with minimal supervision.

Technologies

• Airflow
• dbt
• BigQuery
• GCS
• Pub/Sub
• Dataflow
• Knowledge Catalog DataPlex
• GitHub

Benefits

• Competitive Benefits Package
• Company Contributed 401K Plan
• Paid Time Off and Holidays
• Paid Parental Leave
• Access to Free Tickets to Baseball Games and MLB.TV
• Discounts at MLB Store
• Employee Assistance Programs (EAP)
• Onsite and Online Training & Development Programs
• Tuition Reimbursement
• Disability Benefits (short term and long term)
• Life and Accidental Death Insurance
• Pet Insurance

Nice-To-Have

• A degree in Computer Science, Engineering, or related field, or equivalent practical experience
• Experience with Terraform or other Infrastructure-as-Code tools
• Experience with AI-assisted development or enterprise AI tooling (Gemini Enterprise, Vertex AI)
• A passion for baseball or prior experience in sports, media, or entertainment
• Ability to devise creative solutions for unusual problems

Salary Range

Base salary range: $115,000 - $140,000 per year, plus bonus.

Why MLB?

Major League Baseball is one of the oldest and most storied professional sports leagues in North America. The company emphasizes growth, teamwork, and professionalism across its workforce. Successful employees demonstrate initiative, problem-solving abilities, and a team-first mindset. MLB supports its workforce by engineering experiences that position employees for success and enable high performance.