Job Title: Data Engineer - Python, SQL, Spark, Databricks - Hybrid - Ann Arbor, MI

Location: Ann Arbor, MI - Hybrid - Monday - Thursday On-Site

About the Role: We are seeking a skilled Data Engineer to join our client's cloud transformation initiative, focused on building and optimizing large-scale data pipelines in Databricks . You will play a key role in enabling real-time analytics and machine learning solutions that directly support millions of daily transactions and customer interactions worldwide.

Key Responsibilities: Design, build, and maintain scalable data pipelines using Python , SQL , and Apache Spark within Databricks . Work closely with Data Architects, Data Scientists, and Analysts to ensure data is accurate, available, and high-performing. Integrate diverse data sources into a centralized cloud platform on Microsoft Azure . Implement best practices for data ingestion, transformation, storage, and retrieval. Optimize data workflows for large-scale processing and near-real-time analytics. Ensure compliance with data governance, quality, and security standards.

Required Qualifications: 5+ years of experience in data engineering and pipeline development. Proficiency in Python , SQL , and Apache Spark . Hands-on experience with Databricks (Databricks certification required). Strong understanding of data modeling, ETL/ELT processes, and cloud data architectures. Experience working with high-volume, complex data environments.

Preferred Qualifications: Experience with Azure Data Factory, Azure Synapse Analytics, or Azure Data Lake Storage. Familiarity with real-time data streaming tools (Kafka, Event Hubs, etc.). Exposure to AI/ML data preparation workflows. Background in high-transaction industries such as retail, e-commerce, or QSR.