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INFOSYS NOVA HOLDINGS LLC

Principal Data Engineer

INFOSYS NOVA HOLDINGS LLC
Detroit, MI Full time Posted 45m ago
AWS Cloud Cloud Data Engineering Cloud Data Warehouse Cloud Operations Cloud Platform Cloud Platforms Data Data Analysis Data Analytics Data Architecture Data Engineer Data Engineering Data Integration Data Pipeline Data Platform Data Processing Data Warehouse Data Warehousing Database Databases Dynamodb ETL Informatica Principal Programming Languages Snowflake SQL
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Job Description

The Principal Data Engineer designs, develops, and maintains scalable data solutions for enterprise data engineering and analytics initiatives. The scope covers data engineering, data warehousing, data integration, and cloud-based platforms, with hands-on work across AWS and Snowflake.

Role Focus

In this onsite role based in Detroit, MI, you will build and optimize data pipelines, integration solutions, and analytics-ready data architectures. Responsibilities include ETL/ELT development, data modeling (including Data Vault), orchestration with dbt, and ensuring data quality and governance across complex environments.

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 AWS-based solutions using 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 Qualifications

  • 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 Python and SQL development skills.
  • 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

  • Location: Charlotte, NC / Detroit, MI
  • Work arrangement: Onsite
  • Onsite requirement: Ability to work from the client site on a regular basis

Job Type

Full-Time

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