Skill : Snowflake DBT
Exp : 6 to 12 years
Location : Pune
Key Responsibilities:
Snowflake & DBT Development
Design, develop, and maintain DBT models across staging, intermediate, and mart layers, following modular architecture and industry best practices.
Create and manage DBT assets including tests, documentation, sources, macros, and packages.
Build scalable, reusable, and maintainable data transformation frameworks.
Data Pipeline Engineering
Design, develop, and optimize ELT pipelines using DBT integrated with orchestration tools such as Airflow, Dagster, or Prefect.
Work extensively with AWS and Snowflake-based cloud data platforms.
Develop, maintain, and tune Snowflake schemas, virtual warehouses, and SQL workloads for optimal performance.
Ensure efficient execution of data transformations and analytical queries across the data warehouse.
Data Quality, Security & Governance
Implement and maintain data quality validations within DBT, including uniqueness, null checks, and referential integrity testing.
Contribute to source control, CI/CD processes, documentation standards, and engineering best practices.
Establish monitoring, alerting, and failure-handling mechanisms to ensure pipeline reliability.
Enforce Snowflake security controls such as RBAC, secure views, and cost/performance optimization strategies.
Collaboration & Stakeholder Engagement
Partner with business stakeholders, analysts, and data consumers to gather requirements and translate them into scalable data models.
Deliver well-documented, user-friendly datasets and maintain comprehensive DBT documentation.
Participate in peer code reviews and provide technical mentorship and engineering guidance to team members.
Required Experience & Qualifications
3+ years of experience in Data Engineering, Data Warehousing, or ELT development.
Strong expertise in writing and optimizing complex SQL queries.
Minimum 2 years of hands-on experience with DBT Cloud in a production environment.
Proven experience working with AWS-based data ecosystems and Snowflake data warehousing solutions.
Solid understanding of Git, CI/CD pipelines, and modern data stack practices.
Strong knowledge of dimensional modeling methodologies, including Kimball, Data Vault, Star Schema, and Snowflake Schema designs.
Experience integrating DBT with orchestration platforms such as Airflow, Dagster, or Prefect.
