Senior Data Engineer Snowflake / Azure

This role requires excellent communication skills, as the consultant will work closely with BPOs, Solution Architects, Delivery Leads, and Engineers to explain how solutions should be implemented, why a specific approach is recommended, and the overall goal behind the work being done. The ideal candidate will have hands-on experience designing scalable data pipelines, managing data ingestion frameworks, and delivering high-quality data solutions in a collaborative environment.

Job Title: Senior Data Engineer – Snowflake / Azure
Location : Stillwater MN
Duration : Long Term
Job Description:
We are seeking a Senior Data Engineer with strong expertise in Snowflake, SQL, DBT/Spark, and Cloud platforms to support enterprise data transformation initiatives. The ideal candidate will have hands-on experience designing scalable data pipelines, managing data ingestion frameworks, and delivering high-quality data solutions in a collaborative environment.
This role requires excellent communication skills, as the consultant will work closely with BPOs, Solution Architects, Delivery Leads, and Engineers to explain how solutions should be implemented, why a specific approach is recommended, and the overall goal behind the work being done.
Required Skills:
• Strong hands-on experience with Snowflake
• Advanced SQL expertise
• Experience with DBT or Apache Spark
• Cloud platform experience (Azure preferred, AWS/GCP acceptable)
• Experience with ingestion frameworks such as Fivetran
• Excellent verbal and written communication skills
• Strong stakeholder collaboration experience
Responsibilities:
• Design, build, and optimize scalable ETL/ELT pipelines
• Develop and maintain data models using Snowflake and DBT/Spark
• Implement and support data ingestion frameworks like Fivetran
• Work with cloud-based data platforms, preferably Azure
• Collaborate with business and technical teams to define data requirements
• Clearly explain technical solutions, implementation strategies, and business goals
• Ensure data quality, governance, and performance optimization
• Support solution architecture and data engineering best practices