Data Engineer

In this hands-on Data Engineer role with Major League Baseball's LAI team, you will design and operate production data pipelines on a Google Cloud Platform lakehouse, using Airflow and dbt to empower league analytics. The position is onsite in New York, NY, placing you at the center of MLB’s data-driven decision making.

Responsibilities

• Construct production-grade pipelines with Airflow and dbt to orchestrate batch and streaming transformations across GCP, delivering trusted data to downstream analysts and engineers.
• Design clean, layered data models (staging, intermediate, mart) that serve as the single source of truth for league analytics, applying dbt best practices for materialization, testing, and documentation.
• Operate the ingestion layer using Pub/Sub, GCS, Dataflow, and Knowledge Catalog DataPlex to land both batch and streaming sources into the lakehouse with integrity.
• Establish observability and monitoring standards so data quality issues surface before stakeholders notice them.
• Manage code through GitHub-based CI/CD, contributing to deployment workflows that keep the platform reliable and changes safe.
• Adhere to data governance practices that keep proprietary baseball data secure and compliant.

Requirements

• 2–4 years of production data engineering experience.
• Expert-level SQL, comfortable writing complex freehand queries (sub-queries, nested logic, window functions) and reading others’ code to spot issues.
• Strong Python for data processing, scripting, and automation.
• Hands-on dbt experience — built models across staging, intermediate, and mart layers, wrote tests, and shipped to production.
• Production Airflow experience — DAG authoring, dependency management, 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 — branches, PRs, code review as a daily practice.
• Clear communicator with both engineers and non-engineers, receptive to feedback and able to provide it constructively.
• Execution mindset with the ability to own a project from requirements to deployment with minimal oversight.

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 & MLB.TV
• Discounts at MLB Store | MLBShop.com
• Employee Assistance Programs (EAP)
• Onsite/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 a related field — or non-traditional background with 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). The team is early but ambitious about AI as a lever for engineering efficiency.
• A passion for baseball or prior experience in sports, media, or entertainment.
• Ability to craft creative solutions for unusual problems.

Salary Range

USD 115,000 - 140,000 per year, plus Bonus

Why MLB?

• Major League Baseball is one of the most historic professional sports leagues in North America, with a culture that values growth, teamwork, and professionalism.
• Employees who thrive at MLB tend to take initiative, identify problems, and deliver solutions while prioritizing the team.
• MLB aims to empower its workforce by engineering experiences that position people for success, aligning individual growth with the broader goals of the organization.