Data Engineer
Python
Analytics
Apache Airflow
Automation
Big Data
Bigquery
Cloud
Cloud Dataflow
Data Analysis
Data Analytics
Data Architecture
Data Build Tool
Data Engineer
Data Governance
Data Integration
Data Management
Data Modeling
Data Pipeline
Data Pipelines
Data Platform
Data Processing
Data Security
Data Warehouse
Database
Databases
Dbt
DevOps
ETL
Infrastructure As Code
SQL
Job Description
MLB invites applications for a hands-on Data Engineer to join the LAI team in New York, onsite. The role focuses on building production pipelines with Airflow and dbt on Google Cloud Platform to enable analytics across clubs and the Commissioner's Office.
Responsibilities
- Develop production-grade pipelines with Airflow and dbt to orchestrate batch and streaming transformations on GCP, ensuring downstream analysts and engineers can rely on accurate data without verifying wiring.
- Design layered data models across staging, intermediate, and mart layers to serve as the single source of truth for league analytics, applying dbt best practices for materialization, testing, and documentation.
- Manage the ingestion layer using Pub/Sub, Google Cloud Storage, Dataflow, and Knowledge Catalog DataPlex to land both batch and streaming sources into the lakehouse.
- Establish observability and monitoring standards to surface data quality issues proactively before stakeholders notice them.
- Maintain code through GitHub-based CI/CD, contributing to deployment workflows that preserve reliability and safety of changes.
- Follow data governance practices to keep proprietary baseball data secure and compliant.
Requirements
- 2–4 years of production data engineering experience
- Expert-level SQL, comfortable writing complex freehand queries (subqueries, nested logic, window functions) and reading others' to spot issues
- Strong Python for data processing, scripting, and automation
- Hands-on dbt experience across staging, intermediate, and mart layers, with tests and production deployments
- 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 or Azure with willingness to convert
- Git-based development workflows, including branches, PRs, and code reviews as a daily practice
- Clear communication with engineers and non-engineers, openness to feedback, and collaborative mindset
- Execution mindset with the ability to own a project from requirements to deployment with minimal oversight
Technologies
- Airflow
- dbt
- Python
- SQL
- GitHub
- BigQuery
- GCS
- Pub/Sub
- Dataflow
- Knowledge Catalog DataPlex
- Terraform
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
Salary
Base salary range is USD 115,000 to 140,000 per year, plus bonuses.
Nice to Have
- A degree in Computer Science, Engineering, or a related field, or a 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 in AI adoption and views AI as a lever for engineering efficiency
- A passion for baseball or prior experience in sports, media, or entertainment
- Ability to devise creative solutions for unusual problems
Similar Jobs
