More jobs:
BI Data Engineer II
Job in
Boston, Suffolk County, Massachusetts, 02298, USA
Listed on 2026-08-17
Listing for:
Jobtailor
Full Time
position Listed on 2026-08-17
Job specializations:
-
IT/Tech
Data Engineering
Job Description & How to Apply Below
- 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 Dev Ops and Databricks Asset Bundles where applicable, to improve repeatability and production readiness.
- 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 Dev Ops 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.
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