Data Architect

CumminsIndianapolis, IN
$123,030 - $150,370Remote

About The Position

We are looking for a talented Data Architect to join our team specializing in Systems/Information Technology for Cummins, Inc. as part of DBU Data & Analytics, Remote.

Requirements

  • Talented Data Architect
  • Specializing in Systems/Information Technology
  • Experience with scalable data ingestion and transformation pipelines across relational, event-based, and unstructured sources.
  • Experience building and maintaining frameworks to monitor, detect, and resolve data quality and integrity issues.
  • Experience implementing data governance practices, including metadata management, data access, and retention policies.
  • Experience architecting and guiding development of reliable, efficient, and scalable ETL/ELT data pipelines with monitoring and alerting.
  • Experience designing physical data models and optimizing database structures, indexing, and relationships for performance.
  • Experience testing, optimizing, and troubleshooting data pipelines to ensure stability and performance.
  • Experience developing and managing large-scale data storage solutions using distributed and cloud platforms (e.g., data lakes, Hadoop, NoSQL databases).
  • Experience driving automation and modernization of data infrastructure and integration processes to support agile analytics initiatives.

Responsibilities

  • Design and automate scalable data ingestion and transformation pipelines across relational, event-based, and unstructured sources.
  • Build and maintain frameworks to monitor, detect, and resolve data quality and integrity issues.
  • Implement data governance practices, including metadata management, data access, and retention policies.
  • Architect and guide development of reliable, efficient, and scalable ETL/ELT data pipelines with monitoring and alerting.
  • Design physical data models and optimize database structures, indexing, and relationships for performance.
  • Test, optimize, and troubleshoot data pipelines to ensure stability and performance.
  • Develop and manage large-scale data storage solutions using distributed and cloud platforms (e.g., data lakes, Hadoop, NoSQL databases).
  • Drive automation and modernization of data infrastructure and integration processes to support agile analytics initiatives.
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