Job Description:

We are looking for an AWS Data Engineer with hands on experience in building and managing scalable data pipelines using AWS services PySpark SQL and ETL frameworks
The candidate should have strong data engineering fundamentals and experience working with large scale structured and semi structured datasets

Key Responsibilities:

Design develop and maintain scalable data pipelines on AWS
Develop ETL ELT workflows for data ingestion transformation and processing
Build data processing solutions using PySpark and SQL
Perform data transformations validations and data quality checks
Optimize data pipelines and SQL queries for performance and scalability
Work with different data sources and integrate data into cloud based data platforms
Troubleshoot data pipeline failures and resolve data related issues
Collaborate with business analytics and engineering teams to understand data requirements

Strong hands on experience with AWS Data Engineering services such as S3 Glue Lambda EMR Redshift Athena and IAM
Strong programming experience in PySpark
Excellent knowledge of SQL including complex queries and data transformations
Hands on experience in developing ETL ELT pipelines
Good understanding of data warehousing data lakes and data modeling concepts
Experience handling large scale datasets and optimizing distributed data processing workloads
Knowledge of Python is preferred
Familiarity with Git CI CD orchestration tools and Agile development practices will be an advantage

Good analytical and problem solving skills
Strong communication and collaboration skills
Ability to independently understand requirements and deliver data engineering solutions
Exposure to cloud migration or modernization projects would be an added advantage

Technology->Cloud->AWS