Aws Data Engineer

Role & responsibilities

We are looking for an experienced AWS Data Engineer to design, develop, and maintain scalable data pipelines using AWS services. The role involves building and optimizing ETL/ELT pipelines using AWS Glue, PySpark, Python, and SQL, working with data stored in Amazon S3 and processing data for platforms such as Amazon Redshift and Athena. The candidate will be responsible for data ingestion, transformation, validation, monitoring, troubleshooting, performance optimization, and supporting incremental data processing. The role also involves working with Airflow for workflow orchestration, Lambda for event-driven processing, and collaborating with analysts, developers, and business teams to deliver reliable and high-quality data solutions.

Preferred candidate profile

Candidates should have 36 years of experience in Data Engineering with strong hands-on experience in AWS data services. Good experience with AWS Glue, S3, PySpark, Python, SQL, Redshift, Athena, Lambda, and Airflow is preferred. The candidate should have practical knowledge of ETL/ELT development, data warehousing, incremental loads, data quality, performance tuning, and troubleshooting. Experience working with large datasets, cloud-based data pipelines, and CI/CD or Git-based development is an advantage. Strong problem-solving skills and the ability to work effectively with technical and business teams are expected.