Snowflake DBT Engineer

Job highlights

• 6-12 years experience with Snowflake, dbt, advanced SQL, data modeling, and ETL/ELT expertise
• Develop and optimize data transformation pipelines using Snowflake and dbt; create complex SQL queries and dbt models; implement data quality checks and CI/CD integration; troubleshoot pipeline issues and collaborate with teams

Snowflake + dbt Engineer

Experience: 6-12 Years
Locations: PAN India

Job Summary

We are looking for experienced Snowflake + dbt Engineers with strong hands-on experience in cloud data warehousing, SQL-based data transformation, and data pipeline development. The ideal candidate should have solid expertise in Snowflake and dbt, along with good understanding of data modeling, ETL/ELT, data quality, and CI/CD practices.

Key Responsibilities

• Develop and maintain scalable data transformation pipelines using Snowflake and dbt.
• Create and optimize complex SQL queries, views, tables, CTEs and stored procedures.
• Develop dbt models, macros, snapshots, seeds and tests.
• Implement incremental models and optimize dbt/Snowflake workloads.
• Perform data modeling using dimensional modeling concepts such as Star and Snowflake schemas.
• Implement data quality and validation checks using dbt testing frameworks.
• Manage source-to-target mappings, transformations and data lineage.
• Optimize Snowflake queries, warehouses and overall data processing performance.
• Work with Git and follow version-control and branching practices.
• Support CI/CD integration for dbt deployments.
• Troubleshoot data pipeline failures and production issues.
• Collaborate with data engineers, analysts, architects and business teams.

Mandatory Skills

• Snowflake
• dbt / dbt Core
• Advanced SQL
• Data Warehousing concepts
• Data Modeling
• ETL/ELT concepts
• dbt Models, Tests, Macros and Snapshots
• Snowflake performance optimization
• Git / Version Control

Good to Have

• Python
• Airflow or other orchestration tools
• Azure / AWS / GCP cloud experience
• CI/CD tools such as Jenkins, GitHub Actions or Azure DevOps