BI Data Engineer II

The Boston Beer Company

BI Data Engineer II developing data pipelines and analytics-ready datasets at Boston Beer Company. Contributing to data engineering lifecycle with modern Databricks tools and practices.

Posted 7/27/2026full-timeBoston • Massachusetts • 🇺🇸 United StatesMid-LevelSenior💰 $77,000 - $136,000 per yearWebsite

Tech Stack

Tools & technologies

AzurePySparkPythonSparkSQLUnity

About the role

Key responsibilities & impact

Design, build, test, and support Databricks Lakehouse data pipelines using Spark, Delta Lake, Python, and SQL for reporting, analytics, and downstream business use cases.
Develop and maintain Databricks notebooks, workflows, jobs, and reusable pipeline components following team standards for version control, documentation, testing, and deployment.
Build and maintain curated datasets and analytics-ready models across Lakehouse layers, including bronze, silver, and gold, with attention to data quality, lineage, and business usability.
Support data ingestion, migration, and integration between Databricks, On-Premise SQL Server, SaaS platforms, and other enterprise systems as part of platform modernization.
Partner with analysts, data scientists, business stakeholders, and teams across the Data Enterprise organization, including Data Operations and MDM, to translate requirements into scalable and maintainable data solutions.
Monitor, troubleshoot, and optimize Spark jobs and Databricks workflows for performance, reliability, and cost efficiency under established engineering best practices.
Implement data validation, error handling, data quality checks, security practices, and governance standards across Databricks.
Maintain, administer, and support the evolution of our Databricks platform as a shared responsibility with other team members.
Support CI/CD and automated deployment practices, including Azure DevOps and Databricks Asset Bundles where applicable, to improve repeatability and production readiness.

Requirements

What you’ll need

Bachelor’s degree in Computer Science, a closely related field, or equivalent experience.
Databricks & Spark: Hands-on experience developing data pipelines in Databricks using notebooks, jobs, workflows, PySpark or Spark SQL, and Delta Lake.
Programming & SQL: Strong SQL and Python skills, with the ability to write maintainable transformation logic, troubleshoot data issues, and support production pipelines.
Lakehouse Concepts: Working knowledge of Lakehouse architecture, Delta tables, medallion-style layers, batch processing, and analytics-ready data modeling.
Databricks Platform Exposure: Exposure to one or more Databricks platform capabilities such as Unity Catalog, Delta Live Tables, Databricks SQL, job clusters, workflow orchestration, performance tuning, cluster configuration, administration, or resource provisioning.
Data Quality & Governance: Ability to apply data validation, reconciliation, access controls, documentation, and governance practices to support trusted enterprise data products.
CI/CD & Automation: Exposure to source control and automated deployment practices using tools such as Azure DevOps and Databricks Asset Bundles for reliable, production-ready workflows.
Collaboration & Problem-Solving: Ability to work effectively with analysts, stakeholders, and cross-functional teams to troubleshoot and optimize pipelines.
AI & Analytics: Exposure to AI, machine learning, feature engineering, or analytics frameworks within a modern data platform is a plus.

Benefits

Comp & perks

Generous healthcare on day one
Stock purchase plan
401k
Tuition reimbursement
Fertility/adoption support
Free financial coaching
Health & wellness program and discounts
Professional development & training
Free beer!