Data Analytics Engineer

Compunnel

$95K — $115K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 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.
  • Strong hands-on experience with GitHub.
  • Ability to work effectively in a collaborative, cross-functional team environment.
  • Ability to communicate technical concepts effectively to both technical and non-technical stakeholders.

Responsibilities

  • Design, develop, and maintain star-schema data models, including fact and dimension tables.
  • Build and support DBT models and testing frameworks.
  • Develop, optimize, and troubleshoot data structures and SQL workloads in Snowflake.
  • Apply data modeling best practices for dimensional design, normalization, and denormalization.
  • Partner with stakeholders to translate requirements into scalable analytical solutions.
  • Participate in design discussions and promote consistent data modeling standards.
  • Document modeling decisions and collaborate to improve data architecture practices.

Benefits

  • Collaborative and cross-functional work environment.
  • Opportunities for knowledge sharing and professional growth.
  • Focus on innovative analytical solutions.
  • Engagement with both technical and business stakeholders.
Full Job Description
Job Summary:

The IT - Data Modeler is responsible for building and maintaining the analytical foundation that supports enterprise reporting and analytics. This hands-on role focuses on DBT, Snowflake, SQL, and dimensional data modeling, with an emphasis on designing scalable analytical solutions that align with business processes and use cases. The role partners with technical and business stakeholders to deliver trusted, analytics-ready datasets from ingestion through transformation and into the semantic layer.

Key Responsibilities
• 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 regarding dimensional design, normalization, and denormalization.
• Partner 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 data modeling standards.
• 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 improve data architecture and engineering practices.

Required Qualifications
• 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.
• Strong hands-on experience with GitHub.
• Ability to work effectively in a collaborative, cross-functional team environment.
• Ability to communicate technical concepts effectively to both technical and non-technical stakeholders.

Preferred Qualifications
• Experience with Azure Data Factory (ADF).
• Experience with Python or Power Query.
• DP-203 or SnowPro certification.

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