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Simform

Snowflake Data Engineer

Posted Yesterday
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In-Office or Remote
Hiring Remotely in Ahmedabad, Gujarat
Senior level
In-Office or Remote
Hiring Remotely in Ahmedabad, Gujarat
Senior level
Design, build, and maintain scalable Snowflake data pipelines and dbt transformation workflows. Orchestrate ELT pipelines with Dagster, dlt, and Fivetran; optimize query performance, storage, and data quality; and support governance, security, documentation, troubleshooting, and continuous platform improvement.
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Job Description – Snowflake Data Engineer

We are looking for experienced Snowflake Data Engineers with strong expertise in modern cloud data platforms. The ideal candidate should have hands-on experience in designing and developing scalable data pipelines using Snowflake, dbt, Dagster, dlt, and Fivetran.

Candidates must hold a valid Snowflake Certification, and strong hands-on experience with dbt is mandatory.

Key Responsibilities

  • Design, build, and maintain scalable data pipelines using Snowflake.

  • Develop and optimize data transformation workflows using dbt.

  • Build and orchestrate data pipelines using Dagster.

  • Implement and manage ELT pipelines using dlt and Fivetran.

  • Optimize Snowflake performance, storage, and query execution.

  • Collaborate with business and engineering teams to understand data requirements.

  • Ensure data quality, governance, security, and documentation.

  • Troubleshoot production issues and continuously improve data platform performance.

Required Skills

  • 5+ years of experience in Data Engineering.

  • Strong hands-on experience with Snowflake.

  • Mandatory Snowflake Certification.

  • Strong expertise in dbt (Mandatory).

  • Experience with Dagster orchestration.

  • Experience with dlt (Data Load Tool).

  • Experience with Fivetran.

  • Strong SQL skills.

  • Experience building scalable ELT/ETL pipelines.

  • Knowledge of data modeling, data warehousing, and performance optimization.

  • Strong analytical and problem-solving skills.

Good to Have

  • Experience with cloud platforms (AWS, Azure, or GCP).

  • Experience with CI/CD for data pipelines.

  • Knowledge of Python for data engineering.

  • Exposure to modern data lake and warehouse architectures.

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