Data Engineer at Boston Red Sox in Boston, MA

Summary: Boston Red Sox is seeking a talented self-starter with a background in cloud data architecture to join their Business Strategy & Analytics team as a Data Engineer. This role will support the organization’s Google Cloud Platform data environment and partner with various departments to enhance data-driven decision-making. Responsibilities: - Own, oversee, and support our existing GCP customer data architecture and design decisions - Monitor and address issues as they arise, reducing and eliminating outages for downstream users while also building out monitoring dashboards and alerting systems - Design, build, and maintain reliable ETL pipelines using Python and SQL to ingest new data sources to BigQuery environment - Partner with internal teams to identify, automate, and streamline recurring data workflows - Stay up-to-date on modern trends and solutions in the cloud data architecture space by pursuing educational opportunities both internally and externally - Embed governance, metadata, and data quality controls into data architecture Required Qualifications: - Hands-on experience with cloud-based data warehouses and data lakes across platforms such as GCP, Azure, or AWS - Proficiency in Python and SQL - Experience with ETL frameworks, dbt modeling, CI/CD pipelines, and monitoring tools like Grafana - Experience in maintaining and supporting a complex data environment - Excellent attention to detail and organizational skills - Intellectual curiosity and a strong desire and aptitude to learn new topics and tools - A passion for solving unstructured problems and the ability to take projects from start to finish under tight timelines - Strong communication (written and verbal) and presentation skills - Ability to collaborate successfully with a variety of internal partners and stakeholders Preferred Qualifications: - 1-2 years of work experience preferred but not required Required Skills: Cloud data warehouses, Data lakes, Google Cloud Platform, Azure, AWS, Python, SQL, ETL frameworks, dbt modeling, CI/CD pipelines, Monitoring tools, Grafana, Data governance, Metadata management, Data quality controls, Intellectual curiosity