Description

Design and maintain scalable ETL/ELT data pipelines for enterprise platforms using Snowflake, SQL, and Python on AWS.

Responsibilities

• Build and optimize data models, including staging areas, data warehouses, and data marts, leveraging micro-partitioning and clustering.
• Develop data ingestion workflows for structured and semi-structured sources like JSON, Parquet, XML, and APIs.
• Implement automated data loads and transformations using Snowflake features such as Streams, Tasks, Time Travel, Zero Copy Cloning, and Snowpipe.
• Monitor and troubleshoot pipelines to ensure data quality, integrity, and performance reliability.
• Manage job scheduling and orchestration using industry-standard tools like Tidal.

Required Skills

• 10+ years of experience in data engineering or architecture roles.
• Hands-on expertise with Snowflake cloud database and PL-SQL.
• Strong proficiency in Python for data engineering tasks.
• Proven experience designing and developing ETL/ELT pipelines.
• Deep understanding of data warehousing concepts and data modeling best practices.
• Working knowledge of AWS cloud services.
• Experience with orchestration or scheduling tools.

Preferred Skills

• Familiarity with banking terminology or financial services domain.
• Experience with functional testing for data pipelines.

Key Skills

Education

Any Graduate