Cullerton Group has a new opportunity for a Data Engineer in Chicago, IL. The work will be done onsite three days a week. The rest will be work-from-home. This is a permanent job. Compensation is $130K/yr base salary + 20% bonus. Our customer is a $12bn distributor of building supplies. They have 1,000 branch locations. This work will be done at their downtown location, across the street from Union Station.

Job Summary:

We are seeking a skilled Data Engineer with expertise in Python and Databricks to join our team. This permanent role involves designing, building, and optimizing data pipelines to support advanced analytics, machine learning, and business intelligence initiatives. The ideal candidate will have strong experience with Azure Data Services, Spark, and cloud-based data architectures to enable scalable data solutions.

Key Responsibilities:

• Design and develop scalable data pipelines using Databricks, Python, and Spark.
• Implement ETL/ELT workflows to ingest, transform, and process large datasets from multiple sources.
• Optimize data storage and processing in Azure Data Lake, Delta Lake, and Synapse Analytics.
• Work with structured and unstructured data, ensuring data quality, integrity, and security.
• Develop streaming and batch data processing solutions for real-time and near-real-time analytics.
• Implement best practices in data engineering, including performance tuning and cost optimization.

Required Qualifications:

• 5+ years of experience in data engineering with a strong focus on Python and Databricks.
• Hands-on experience with Apache Spark, including performance optimization and tuning.
• Proficiency in Azure Data Services (Azure Data Lake, Synapse, Data Factory).
• Experience with SQL and NoSQL databases for data modeling and querying.
• Strong understanding of data architecture, ETL/ELT pipelines, and data warehousing concepts.