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Snowflake Data Engineer

Exclusive opportunity

Remote

Snowflake Data Engineer

AiHR Enterprises Pvt Ltd

Snowflake Data Engineer

Skills

Google Cloud PlatformSQL QueriesData EngineeringPythonSnowflakeAWSdbtAzure

2 months ago

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Important information


Contract type:

Temporary

Location:

India

Work mode:

Remote

Published on:

21 August 2026

What they need


Job Title: Snowflake Data Engineer Location: 100% Remote role (Across India) Contract role for 2-3 months initially. 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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