Senior Data Engineer (Azure Databricks)

Location: Chicago, IL (Hybrid – 3 days onsite, 2 days remote)
Job Type: Full-Time / Direct Hire
Salary: $148,000 - $164,000 (DOE)

We are seeking a highly skilled Senior Data Engineer to join a growing data engineering team. The ideal candidate will have strong experience designing, building, and maintaining scalable end-to-end data pipelines in modern cloud environments, with expertise in Azure Databricks.

Responsibilities

• Design, develop, and maintain scalable end-to-end data pipelines.
• Build data ingestion, validation, transformation, and governance frameworks.
• Develop reusable, metadata-driven data pipeline solutions.
• Optimize data processing performance and troubleshoot complex data issues.
• Design and implement scalable data architecture to support business needs.
• Collaborate with cross-functional teams to deliver reliable data solutions.
• Implement data quality, monitoring, and testing best practices.
• Work with cloud-native data platforms and services to support enterprise analytics.

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related field.
• 6+ years of hands-on experience building and owning end-to-end data pipelines.
• Expert-level proficiency in Python and SQL.
• Strong experience with data ingestion, transformation, validation, and governance.
• Ability to design scalable data architectures and clearly communicate technical solutions.
• Experience building reusable, metadata-driven pipelines.
• Strong troubleshooting, debugging, and performance optimization skills.
• Hands-on experience with data modeling, testing, monitoring, and data quality practices.

Preferred Qualifications

• Strong experience with Azure Databricks (required/preferred platform).
• Experience with Azure Data Factory and other Azure cloud data services.
• Familiarity with enterprise data engineering best practices and cloud-native architectures.

Work Arrangement

• Hybrid schedule: 3 days onsite per week in Chicago, IL.
• Local candidates are strongly preferred.