Description

Job Responsibilities include:

Design, develop, and maintain scalable ETL/ELT data pipelines using PySpark, SQL, and Snowflake.

Ingest and transform data from multiple sources, including APIs, flat files, and relational databases.

Develop and manage data models, including Fact and Dimension tables, using Star and Snowflake schema designs.

Monitor and optimize Snowflake queries and Spark jobs to improve performance, scalability, and cost efficiency.

Implement data quality checks, validation frameworks, and testing procedures to ensure data accuracy and reliability.

Troubleshoot production issues, support pipeline operations, and manage code versioning using Git.

Required Qualifications:

Bachelor’s degree in computer science, Information Technology, Data Engineering, or a related field.

6–8 years of experience in Data Engineering and data pipeline development.

Strong hands-on experience with Snowflake, PySpark, SQL, and building scalable ETL/ELT data pipelines.

Proven expertise in data modeling, performance optimization, data quality frameworks, and troubleshooting production data environments

Key Skills

Education

Any Graduate