Description

You will own the analytics engineering lifecycle, building scalable data models and transformations using dbt and Snowflake. You ensure data reliability, performance, and governance across the stack.

Responsibilities

• Design, develop, and optimize data models and transformations using dbt following analytics engineering best practices.
• Build and manage scalable cloud data warehouse solutions on Snowflake, optimizing performance via clustering, warehouse sizing, and caching.
• Develop complex, high-performance SQL queries for data transformation, analysis, and reporting.
• Implement data quality checks, testing, and documentation using dbt tests and exposures.
• Manage and maintain data pipelines ensuring reliability, accuracy, and timeliness while implementing CI/CD workflows.

Required Skills

• 5+ years of experience as a Software Engineer or Analytics Engineer.
• Deep expertise in Snowflake architecture, performance tuning, and cost control.
• Proficiency in dbt for data transformation, testing, and deployment workflows.
• Strong SQL skills for complex data transformations and analysis.
• Experience with Python for data engineering tasks.
• Knowledge of CI/CD practices for data models.
• Familiarity with cloud platforms such as AWS or Azure.

Preferred Skills

• Experience integrating Snowflake with BI tools like Power BI or Tableau.
• Knowledge of semi-structured data formats (JSON, Parquet) in Snowflake.
• Understanding of ELT architecture and modern data stack concepts.

Key Skills

Education

Bachelor's degree