Conexess
Data Engineer - Python, SQL, Spark, Databricks - Hybrid - Ann Arbor, MI
Conexess, Ann Arbor, Michigan, us, 48113
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.
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.