Sr. Data Engineer, Baseball Systems

DEPARTMENT OVERVIEW:

Members of the Baseball Systems team at the Boston Red Sox are focused on designing, building, and refining the software and data pipelines used within Baseball Operations. These tools and applications are an integral part of the decision-making process, are directly integrated in the workflows of all departments within Baseball Operations, and provide an efficient, consistent, and accessible experience when interacting with our internal data sources and applications.

POSITION OVERVIEW:

The Boston Red Sox are seeking a Senior Data Engineer, Baseball Systems who is a hands-on database expert responsible for administering and optimizing large-scale SQL environments, building robust data pipelines, and ensuring high-performance access to critical baseball operations data across on-prem and cloud platforms.

The ideal candidate thrives in a fast-paced environment, is comfortable managing both modern Snowflake-based pipelines and legacy SQL Server systems, and brings a strong sense of ownership to delivering scalable, efficient, and maintainable data solutions that directly impact decision-making throughout Baseball Operations. This role is central to the reliability and evolution of the Red Sox’s data infrastructure, supporting analysts, developers, and systems engineers across player evaluation, baseball sciences, and scouting domains.

• Administer and optimize Snowflake and SQL Server environments, including warehouse sizing, query tuning, and access control policies
• Develop robust data transformation pipelines, leveraging data from both APIs and file-based sources
• Leverage tools like dbt, Snowpipe, and Snowpark for data transformations
• Design, manage, and monitor data pipelines that move structured and unstructured data from Azure Blob Storage into Snowflake, ensuring reliability, performance, and cost-efficiency
• Maintain and modernize legacy SQL Server data pipelines, improving performance through query optimization, indexing strategies, and resource tuning
• Contribute to the infrastructure design and software lifecycle phases—including technical design, testing, implementation, and quality assurance
• Provide proactive support for critical production systems, resolving pipeline or performance issues quickly and effectively
• Partner with software developers, analysts, and other stakeholders to support analytical, operational, and reporting needs across Baseball Operations
• Participate in code reviews, architecture discussions, and DevOps best practices with the data engineering and software development teams

• Aptitude and ability to apply academic or applied experience in software development or data engineering related field.
• An advanced understanding of modern databases, SQL and query optimizations, stored procedures, views, and other db objects
• Able to design data solutions to allow for cost-effective, scalable, fast, and flexible solutions to support front-end development, analyst work, and data health and monitoring needs
• Able to pick up quickly and think both creatively and critically to solve problems
• A basic understanding of contemporary baseball and/or sports analysis and development practices
• A team-player that collaborates effectively with technical and non-technical stakeholders

• Bachelor’s degree in Computer Science, Software Engineering, Computer Engineering, or a related technical field
• 3-5 years of experience in a data engineering or data platform role with a focus on database performance and pipeline reliability
• Strong SQL development and optimization skills, including experience with stored procedures, indexing, and query tuning in SQL Server
• Hands-on experience administering and developing in Snowflake, including warehouse scaling, role-based access, and usage monitoring
• Proficiency in building and maintaining data pipelines from Azure Blob Storage to Snowflake, using tools like dbt, Snowpipe (or equivalent)
• Solid understanding of ELT/ETL concepts and data architecture best practices across cloud and hybrid systems
• Familiarity with DBT for data transformation and modeling is strongly preferred
• Experience with GraphQL is a plus but not required
• Ability to work autonomously and as a team in a fast paced environment
• High level of attention to detail with the ability to multi-task effectively
• Comfortable working remotely when required and using Zoom, Teams, Slack, Trello, and other tools to communicate with all team members
• High degree of professionalism and ability to maintain confidential information
• Excellent organizational and time management skills