Data Engineer

Major League Baseball is seeking a hands-on Data Engineer to join the LAI team and shape production data pipelines that power league analytics. This onsite role in New York, NY centers on building and operating a GCP lakehouse with Airflow and dbt to deliver trusted data for analysts and engineers. You will own the end-to-end data workflow from ingestion to production monitoring.

Responsibilities

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

Requirements

• 2 to 4 years of hands-on production data engineering experience.
• Advanced SQL skills, able to craft complex queries (subqueries, nested logic, window functions) and review others' queries for issues.
• Proficient Python for data processing, scripting, and automation.
• Hands-on dbt experience building models 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.
• Experience with Git-based development workflows including branching, pull requests, and code reviews as a daily practice.
• Clear communicator with both engineers and non-engineers, receptive to feedback, and constructive in responses.
• Execution-oriented mindset, able to own projects 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)
• A passion for baseball or prior experience in sports, media, or entertainment
• Ability to build creative solutions for unusual problems

Salary

USD 115,000 - 140,000 per year, plus bonus.

Why MLB?

Major League Baseball is the historic centerpiece of professional sports in North America, known for a culture that emphasizes growth, teamwork, and professionalism. Employees thrive by taking initiative, solving problems, and putting the team first. MLB aims to empower its workforce to excel by offering experiences that position them for success.