Snowflake Data Engineer

We are looking for a skilled Data Engineer with strong hands-on experience in Dbt and Snowflake to deliver modern data warehousing solutions for our global clients. You will work on end-to-end implementations, from data ingestion and modeling to performance tuning, in collaboration with client stakeholders.

Key Responsibilities:

• Design, build, and maintain modular dbt models (staging, intermediate, and mart layers) on Snowflake.
• Develop and manage ELT pipelines that ingest data from sources like databases, APIs, and SaaS tools using Fivetran, Airbyte, Snowpipe, or similar.
• Implement dimensional models (star schema, fact and dimension tables), incremental models, and SCD Type 2 using dbt snapshots.
• Write dbt tests, documentation, and source freshness checks to make sure data is accurate and traceable.
• Optimize Snowflake performance and cost through warehouse sizing, clustering, query profiling, and resource monitors.
• Manage Snowflake objects and features, including RBAC, streams, tasks, stored procedures, Time Travel, and zero-copy cloning.
• Set up and maintain CI/CD for dbt projects using Git and GitHub Actions, Azure DevOps, or dbt Cloud.
• Orchestrate pipelines using Airflow, dbt Cloud jobs, or Dagster.
• Partner with analysts and business teams to translate requirements into scalable data models.
• Take part in code reviews and help define data engineering standards and best practices.

Must-Have Skills

• 4+ years in data engineering, with at least 2 years of hands-on dbt (Core or Cloud) experience in production.
• Strong SQL skills, including CTEs, window functions, and query optimization.
• Hands-on Snowflake experience: virtual warehouses, RBAC, Snowpipe, streams and tasks, and performance tuning.
• Working knowledge of Jinja, dbt macros, and packages like dbt_utils.
• Solid understanding of data modeling (Kimball methodology, SCDs, fact and dimension design).
• Experience with Git-based workflows and CI/CD.
• Python for scripting and automation.
• Experience with at least one cloud platform (AWS, Azure, or GCP).