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
Join MLB's LAI team as a hands-on data engineer shaping production pipelines with Airflow and dbt on GCP to power analytics across clubs and the Commissioner's Office.
Responsibilities
- Build production-grade pipelines using Airflow and dbt to orchestrate batch and streaming transformations across GCP, so downstream analysts and engineers can trust the data they query without checking the wiring.
- Architect 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 cleanly into the lakehouse.
- Implement observability and monitoring standards so that data quality issues surface before stakeholders notice them.
- Manage code through GitHub-based CI/CD, contributing to deployment workflows that keep our platform reliable and our 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 someone else’s to spot issues.
- Strong Python for data processing, scripting, and automation.
- Hands-on dbt experience — built models across staging, intermediate, and mart layers, written 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 reviews as a daily practice.
- Clear communication with both engineers and non-engineers, receptive to feedback and able to give it kindly.
- Execution mindset. You can 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 & 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
Salary
Base salary: USD 115,000 - 140,000 per year, plus bonus.
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.
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