Live opening · Posted 1 day ago

Senior Snowflake Data Engineer

EliteSquad.AI · India (Remote)
Linkedin No
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At a glance

The key details from the original listing.

Posted 1 day ago
CompanyEliteSquad.AI
LocationIndia (Remote)
Work modeNo
SourceLinkedin
Listed1 day ago

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About the role

Description supplied by the original job listing.

Role: Snowflake Data Engineer
Experience: 6+ Years
Work Mode: Remote
Working Hours: Regular Shift 10 to 7 PM IST
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
7+ 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.

Work arrangement
No

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