Snowflake Data Engineer - ETL
LocationHyderabad, Telangana, India
Typefull-time
DepartmentJonali
Company size1,001–5,000 people
PostedJun 18, 2026 · 3mo ago
Verified live22h ago
At a glanceSummarised by Seekless from the posting.
Strong experience in ETL/ELT development
Data modeling skills
SQL optimization skills
Experience with cloud-based data warehousing
Design, develop, and maintain scalable data solutions on the Snowflake platform
Develop complex SQL queries, stored procedures, views, and performance tuning strategies
Design conceptual, logical, and physical data models for enterprise data warehousing
Implement data integration processes from multiple source systems
Create and maintain dimensional models (Star Schema, Snowflake Schema)
Develop incremental and full-load ETL processes
Monitor and troubleshoot data pipeline failures and performance issues
Ensure data quality, governance, security, and compliance standards
Collaborate with business analysts and stakeholders to understand reporting and analytics requirements
Participate in code reviews, deployment activities, and production support
Document data flows, mappings, and technical specifications
Skills
Snowflake
ETL
ELT
SQL
Stored Procedures
Views
Data Modeling
Star Schema
Snowflake Schema
Job Summary
We are seeking a highly skilled Snowflake Data Engineer to design, develop, and maintain scalable data solutions on the Snowflake platform. The ideal candidate will have strong experience in ETL/ELT development, data modeling, SQL optimization, and cloud-based data warehousing. You will work closely with business stakeholders, data analysts, and engineering teams to build robust data pipelines and ensure high-quality data delivery.
Key Responsibilities
•
Design, develop, and maintain scalable data pipelines using Snowflake and ETL/ELT tools.
•
Build and optimize data warehouse solutions on Snowflake.
•
Develop complex SQL queries, stored procedures, views, and performance tuning strategies.
•
Design conceptual, logical, and physical data models for enterprise data warehousing.
•
Implement data integration processes from multiple source systems.
•
Create and maintain dimensional models (Star Schema, Snowflake Schema).
•
Develop incremental and full-load ETL processes.
•
Monitor and troubleshoot data pipeline failures and performance issues.
•
Ensure data quality, governance, security, and compliance standards.
•
Collaborate with business analysts and stakeholders to understand reporting and analytics requirements.
•
Participate in code reviews, deployment activities, and production support.
•
Document data flows, mappings, and technical specifications.