Description

You will design, build, and optimize scalable data transformation pipelines and ensure data quality across analytics platforms.

Responsibilities

• Design and implement modular, reusable DBT models including staging, intermediate, and mart layers.
• Build and maintain ELT pipelines using Snowflake native features like Snowpipe, Streams, and Tasks.
• Optimize Snowflake performance through clustering, partitioning, caching, and query tuning.
• Automate workflows using orchestration tools and implement CI/CD pipelines for DBT projects.
• Collaborate with architects and stakeholders to translate business requirements into scalable data solutions.

Required Skills

• 8+ years of professional experience in data engineering.
• 3-6 years of hands-on experience with Snowflake, including SnowSQL, Snowpipe, Streams, Tasks, and Time Travel.
• 2 years of hands-on experience with DBT Core or Cloud in a production environment.
• Strong SQL skills and expertise in data modeling (star/snowflake schema, normalization/denormalization).
• Deep understanding of DBT features, including materializations, macros, seeds, snapshots, and tests.
• Proficiency with Git, CI/CD, and workflow orchestration.
• Experience integrating Snowflake with cloud storage such as AWS S3, Azure Blob, or GCP.
• Hands-on experience with ELT pipelines and SAP ECC/S4 HANA data sources.

Preferred Skills

• Experience with Airflow or Azure Data Factory.
• SnowPro Core Certification.

Key Skills

Education

Any Graduate