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Principal Data Engineer Snowflake / AWS / Data Vault

ICONMA, LLC

  • Detroit, MI
  • 1 day ago
  • $53.57 Per Hour

Highlights

Ability to evaluate emerging tools, technologies, and architectural approaches, and recommend scalable solutions that improve performance, maintainability, and long-term supportability. Proven ability to influence, advise, and partner effectively with senior business and technology stakeholders to identify strategic challenges, assess options, and recommend solutions.

Numbers & Facts

LocationDetroit, MI
Salary$53.57 Per Hour

Description

Our client, a IT Services and Consulting company, is looking for a Principal Data Engineer – Snowflake / AWS / Data Vault for their Detroit, MI/Hybrid location.
 
Responsibilities:
  • Design, build, and optimize modern data pipelines and enterprise data solutions that support analytics, reporting, data science, and AI use cases.
  • Develop and implement cloud-based data engineering solutions, including data lakes, cloud data warehouses, and enterprise data platforms.
  • Design scalable data structures and support enterprise data storage using Data Vault modeling to enable flexible, auditable, and resilient data solutions.
  • Build and support data ingestion, transformation, preparation, and quality processes across structured and unstructured data sources.
  • Develop robust solutions for large-scale data integration, relational and NoSQL data processing, and API-based data services.
  • Enable trusted, high-quality, and accessible data for analytics, machine learning, and AI-driven business capabilities.
  • Partners with business and technology teams to define data requirements, transformation rules, integration needs, and solution designs that align to enterprise and line-of-business priorities.
  • Help advance Insurance Data and Analytics platform capabilities through scalable engineering, strong data foundations, and governance-aligned practices.
  • Establish and maintain data quality, validation, monitoring, metadata, and lineage processes to support reliable and well-managed enterprise data assets.
  • Apply modern software engineering methods and Agile practices to deliver scalable, reliable, and maintainable data solutions.
  • Promote engineering, operational, and design standards across data platforms and services.
  • Evaluate and recommend tools, technologies, and approaches that improve performance, delivery, and long-term supportability.
  • Collaborate across business and IT teams to solve complex technical challenges and deliver practical, scalable solutions.
  • Support enterprise data governance, data management, and data security requirements.
  • Provide technical leadership, mentor team members, and contribute to strong delivery outcomes through effective collaboration and sound engineering practices.
 
Requirements:
  • Bachelor’s degree in computer science, Information Systems, or a related field; advanced degree preferred.
  • 10+ years of progressive experience in data engineering, including deep expertise in analytics-focused data warehouse environments such as Snowflake.
  • Extensive hands-on experience designing and delivering cloud-based data solutions on AWS, including services such as S3, AWS CLI, Lambda, and DynamoDB.
  • Strong experience with modern data engineering and integration tools such as dbt, Qlik Replicate, InfoSphere DataStage, and CP4D.
  • Deep expertise in data modeling, including Data Vault, and in designing scalable, auditable, and resilient data structures that support enterprise analytics, reporting, and AI use cases.
  • Proven experience architecting and optimizing large-scale data ingestion, transformation, cleansing, standardization, and deduplication processes across complex data environments.
  • Strong programming and automation skills in Python and other scripting languages used to support enterprise data engineering solutions.
  • Demonstrated experience leading the design and implementation of enterprise data pipelines using Git, DevOps practices, and modern software engineering approaches.
  • Strong background in large-scale data integration, API development, and data migration across distributed systems and platforms.
  • Deep understanding of data governance, data management, metadata, lineage, and data security, with the ability to embed these practices into engineering solutions.
  • Proven ability to lead end-to-end solution delivery, working independently while providing technical direction across multiple initiatives and technologies.
  • Demonstrated success establishing and enforcing engineering, design, and operational standards across teams and platforms.
  • Ability to evaluate emerging tools, technologies, and architectural approaches, and recommend scalable solutions that improve performance, maintainability, and long-term supportability.
  • Proven ability to influence, advise, and partner effectively with senior business and technology stakeholders to identify strategic challenges, assess options, and recommend solutions.
  • Strong track record of mentoring engineers, promoting engineering excellence, and contributing to high-performing teams.
  • Extensive experience across the full software development lifecycle, including architecture, design, implementation, testing, deployment, and operational support.
  • Knowledge of the insurance business data domain is a major plus, including familiarity with insurance data concepts, business processes, and analytics use cases.
  • Ability to design trusted, high-quality data foundations that enable advanced analytics, machine learning, and AI-driven business capabilities.
  • Strong problem-solving, communication, and leadership skills, with the ability to translate complex technical concepts into practical business solutions.
  • Insurance Business data domain knowledge.
  • 12.00 Years of Experience
 
Why Should You Apply?  
 

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