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LEAD SNOWFLAKE DATA ENGINEER (Minneapolis)
LEAD SNOWFLAKE DATA ENGINEER (Minneapolis)KPG99 INC • Minneapolis, MN, United States
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LEAD SNOWFLAKE DATA ENGINEER (Minneapolis)

LEAD SNOWFLAKE DATA ENGINEER (Minneapolis)

KPG99 INC • Minneapolis, MN, United States
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Job Title : Lead Snowflake Data Engineer

Employment Type : 6-month Contract-to-Hire

Work Arrangement : On-site (4 days / week)

Location : Downtown Minneapolis, MN (Local candidates only)

Eligibility : U.S. Citizen or Green Card holders only

Experience Level : 7+ years

Role Overview

We are seeking a Lead Snowflake Data Engineer to design, build, and optimize modern cloud-based data platforms. This role requires deep hands-on expertise with Snowflake, strong SQL skills, cloud data engineering experience, and the ability to lead and mentor a team of data engineers.

Required Qualifications

  • 7+ years of experience in data engineering or related roles
  • 510 years of hands-on experience with Snowflake
  • Strong proficiency in SQL, including complex query development and stored procedures
  • Experience with automation and scripting (e.g., Python, Shell, or similar)
  • Hands-on experience with data ingestion and transformation frameworks
  • Strong understanding of Snowflake architecture, including storage, compute, security, and infrastructure
  • Proven experience with Snowflake troubleshooting and performance tuning
  • Experience with cloud platforms such as AWS and / or Azure
  • Solid understanding of Cloud Data Lakehouse architectural patterns
  • Experience leading, mentoring, and providing technical direction to data engineering teams
  • Proven ability to work closely with business partners to develop and manage data domains

Preferred / Additional Skills

Experience in one or more of the following areas is highly desirable :

  • Programming languages (e.g., Python, Java, Scala)
  • Relational and non-relational databases
  • ETL / ELT tools and frameworks
  • Data storage solutions (on-premises and cloud-based)
  • Big data technologies
  • Machine learning or advanced analytics
  • Data modeling and data visualization tools
  • Cloud computing and data security best practices
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