Principal Data Engineer

INFOSYS NOVA HOLDINGS LLC is seeking a Principal Data Engineer to design, build, and keep scalable data solutions running for enterprise data engineering and analytics initiatives. In this Detroit, MI onsite role, you will work across data engineering, data warehousing, data integration, and cloud technologies, including AWS and Snowflake.

The position focuses on end-to-end pipeline and platform work: from architecture and modeling through ETL/ELT implementation, transformation workflows, data quality and governance, and ongoing troubleshooting across complex environments. You will also provide technical guidance to support engineering best practices as solutions evolve.

Responsibilities

• Design, develop, and optimize scalable data pipelines and data integration solutions.
• Develop and maintain data architectures for enterprise data warehouses, data lakes, and analytics platforms.
• Build and optimize ETL/ELT processes using modern data engineering tools and technologies.
• Develop solutions using AWS services including S3, Lambda, and DynamoDB.
• Design and implement data solutions within Snowflake and other cloud-based data environments.
• Develop and maintain data models, including Data Vault modeling methodologies.
• Write and optimize complex SQL and Python code for data processing and integration.
• Use dbt to develop, transform, test, and manage data workflows.
• Support data replication and integration using tools such as Qlik Replicate.
• Work with enterprise data platforms including IBM InfoSphere DataStage and CP4D.
• Develop and integrate APIs to support enterprise data and application needs.
• Establish and maintain data quality, governance, metadata management, and data lineage processes.
• Collaborate with engineering, architecture, analytics, and business teams to translate requirements into scalable data solutions.
• Troubleshoot performance, data quality, and integration issues across complex data environments.
• Provide technical leadership and guidance on data engineering architecture and best practices.

Requirements

• Strong experience in data engineering and enterprise data environments.
• Hands-on experience with AWS, particularly S3, Lambda, and/or DynamoDB.
• Strong experience with Snowflake and cloud data warehousing.
• Advanced skills in Python and SQL.
• Experience developing ETL/ELT and data integration solutions.
• Experience with data warehousing and data modeling, including Data Vault.
• Experience with dbt or similar modern data transformation frameworks.
• Experience with data quality, governance, metadata management, and data lineage.
• Strong understanding of relational and non-relational databases.
• Experience with enterprise data integration platforms and tools.
• Ability to work independently while providing technical leadership to other engineers.

Technologies

• AWS, S3, Lambda, DynamoDB
• Snowflake
• Python, SQL
• ETL/ELT
• dbt
• Qlik Replicate
• IBM InfoSphere DataStage, CP4D
• Data Vault
• APIs

Location and Work Arrangement

• Onsite in Detroit, MI.
• Location listing also indicates Charlotte, NC/Detroit, MI.

Employment Type

• Full-Time.

Work Environment

This is an onsite position that requires the ability to work from the client site on a regular basis.