Principal Data Engineer

The Principal Data Engineer role at INFOSYS NOVA HOLDINGS LLC focuses on designing, building, and maintaining scalable data solutions that support enterprise data engineering and analytics initiatives. This position spans data engineering, data warehousing, data integration, and cloud-based implementations, leveraging AWS and Snowflake to deliver reliable platforms and governed data flows.

This is a full-time, onsite opportunity based at the client site, with location options listed as Charlotte, NC and Detroit, MI, and a primary location noted for Detroit, MI.

What you will do

• Design, develop, and optimize scalable data pipelines and data integration solutions.
• Build and maintain data architectures for enterprise data warehouses, data lakes, and analytics platforms.
• Create 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.

Required skills and experience

• 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 development.
• 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 you will work with

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

Work arrangement and job type

• Onsite: Ability to work from the client site on a regular basis.
• Full-Time