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.