Data Engineer – Python, SQL, Spark, Databricks – Hybrid – Ann Arbor, MI

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:

• + 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.