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# Snowflake Data Engineer

- **Company:** Pantheon Inc
- **Location:** United States
- **Contract:** Permanent contract
- **Skills:** Adobe InDesign, Data Analysis, Business Intelligence Development, Data Architecture, Data Structures, Data Warehousing, Python (Programming Language), SQL Databases, Azure Data Factory, Sql Optimization, Snowflake, Powerquery, Data Analytics, Data Delivery
- **Published:** August 14, 2026
- **Apply:** https://www.dice.com/job-detail/f75de4d0-3482-4c7b-9d20-9fddee90c2e3

## About the Role

We are looking for a hands-on Data Analytics Engineer with strong experience in DBT, Snowflake, and dimensional data modeling to help build and maintain the analytical foundation that supports enterprise reporting and analytics., A collaborative analytics engineer who enjoys working with teammates and stakeholders to transform complex source data into well-designed star-schema models using DBT and Snowflake, while contributing to a strong engineering culture and data modeling best practices, Strong hands-on experience with DBT development and testing.

 - Strong experience with Snowflake and SQL optimization.
 - Proven experience designing and implementing star-schema dimensional models.
 - Deep understanding of fact and dimension modeling and analytical data warehouse concepts.
 - Ability to work effectively in a collaborative, cross-functional team environment and communicate technical concepts to both technical and non-technical stakeholders.

Preferred Qualifications:

 - Azure Data Factory (ADF)
 - Power BI Semantic Models
 - Python or Power Query
 - DP-203 or SnowPro certifications

## Description

Design, develop, and maintain star-schema data models, including fact and dimension tables.

 - Build and support DBT models and testing frameworks to deliver trusted, analytics-ready datasets.
 - Develop, optimize, and troubleshoot data structures and SQL workloads in Snowflake.
 - Apply data modeling best practices and make informed decisions around dimensional design, normalization, and denormalization.
 - Partner closely with Data Engineers, BI Developers, Product Owners, and business stakeholders to translate requirements into scalable analytical solutions.
 - Participate in design discussions, knowledge sharing, and peer reviews to promote consistent modeling standards across the team.
 - Support data delivery from ingestion through transformation and into the semantic layer for reporting and analytics.
 - Document modeling decisions and collaborate with team members to continuously improve data architecture and engineering practices.


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