Description

Key Skills: AWS, Redshift, Pyspark, Databricks, SQL

Roles and Responsibilities:

• Develop and maintain data pipelines on AWS using AWS Glue and PySpark.
• Build and optimize data models and transformations for analytics in Amazon Redshift.
• Implement scalable batch data processing jobs and data ingestion workflows.
• Write and tune SQL for data extraction, validation, and analytics enablement.
• Collaborate with analytics and engineering teams to deliver production-ready datasets.

Skills Required:

• 5-8 years of experience in Data Engineering
• Strong hands-on experience with AWS
• Experience with AWS Glue for data integration and ETL
• Strong knowledge of PySpark and distributed data processing
• Hands-on experience with Amazon Redshift
• Experience building and maintaining scalable data pipelines
• Strong SQL skills for data extraction, transformation, and validation
• Experience with batch processing and data ingestion
• Good understanding of data modeling and data warehousing

Good to Have:

• Experience with Databricks
• Knowledge of AWS data services such as S3, Lambda, and EMR
• Experience with data analytics and production data pipelines
• Knowledge of ETL/ELT processes

 Education: Bachelor's Degree in Computer Science or related field; Master's Degree in Data Science preferred

Key Skills

Education

Any Graduate