Data Engineer

iMPact Business Group; Grand Rapids (MI); On-site; USD 110,000 - 160,000; Full time

Job summary

Impact Business Group is seeking a Databricks Data Engineer to build and optimize production data pipelines within the Databricks Lakehouse architecture. You will implement bronze, silver, and gold layers, ensuring data quality and lineage across ERP/CRM sources.

The role requires hands-on experience with Delta Lake, PySpark, and Databricks Workflows, plus knowledge of Unity Catalog and Azure data services. You will collaborate closely with the Data Engineering & Platform team.

Qualifications

• 3 years data engineering experience, incl. 2+ years with production Databricks pipelines.
• Experience implementing bronze/silver/gold with Delta Lake.
• Strong SQL, Python, PySpark; able to orchestrate pipelines.
• Knowledge of Unity Catalog and Azure data services.
• Bachelor's degree or equivalent.

Responsibilities

• Build and improve production data pipelines in Databricks across bronze, silver, and gold layers.
• Land raw data in bronze, validate and standardize in silver, publish curated models in gold.
• Review notebooks, pipelines, and data models built by partners.
• Trace dependencies, fix gaps, and document operation and troubleshooting steps.
• Monitor job failures and data freshness; add automated checks.

Skills

SQL

Python

PySpark

Databricks

Azure

Education

Bachelor's degree in a related field

Tools

Delta Lake

Unity Catalog

Databricks Workflows

Azure Data Factory

Azure Data Lake Storage

Job description

Databricks Data Engineer

Our client is hiring a Data Engineer to build and improve production pipelines in Databricks. You'll work across the bronze, silver, and gold layers of the lakehouse and help take ownership of existing pipelines. This is a hands‑on individual contributor role reporting to the Data Engineering & Platform Manager.

What You'll Do

• Build batch and incremental pipelines that bring data from ERP, CRM, and other operational systems into the Databricks Lakehouse.
• Use medallion architecture to land raw data in bronze, validate and standardize it in silver, and publish curated models in gold for reporting and analytics.
• Review existing notebooks, pipelines, and data models built by implementation partners.
• Trace dependencies, fix gaps, and document how to operate and troubleshoot them.
• Monitor job failures and data freshness.
• Troubleshoot root causes and add automated checks to validate data and reconcile it to source systems.
• Apply Unity Catalog standards for access controls, ownership, and lineage.
• Use Git, code review, and CI/CD to deploy changes.

What You’ll Bring

• Approximately 3 years of data engineering experience, including at least 2 years building production pipelines in Databricks.
• Hands‑on experience implementing bronze, silver, and gold layers using Delta Lake.
• Strong SQL, Python, and PySpark skills, with experience orchestrating pipelines in Databricks Workflows or Lakeflow Jobs.
• Working knowledge of Unity Catalog and Azure data services such as Azure Data Lake Storage or Azure Data Factory.
• Bachelor's degree in a related field or equivalent practical experience.