Our client is seeking an experienced AWS Data Engineer with 4+ years of hands-on Data Engineering experience. The ideal candidate should have robust expertise in Python, PySpark, SQL, and AWS services, with experience building scalable data pipelines and cloud-based data solutions.
This role focuses on data ingestion, transformation, storage, and analytics, with an emphasis on data quality, reliability, performance, and cost optimization.

Key Responsibilities
Design, develop, and maintain scalable data pipelines using Python and PySpark.
Build and optimize ETL/ELT workflows for data ingestion, transformation, and processing.
Write and optimize complex SQL queries for data transformation, validation, and analytics.
Build and manage cloud-based data solutions using AWS Glue, S3, Redshift, Athena, and Lambda, with SNS, SQS, CloudWatch, EventBridge, and API Gateway supporting integration, automation, and monitoring.
Ensure data quality and troubleshoot pipelines to improve reliability, performance, and cost efficiency.




Collaborate with cross-functional teams to translate business requirements into scalable data solutions.

Required Skills
4+ years of hands-on experience in Data Engineering.
Strong understanding of data ingestion, transformation, ETL/ELT, data quality, data modeling, and pipeline optimization.
Strong hands-on experience with Python and PySpark for data processing.
Robust practical knowledge of SQL, including complex queries and query optimization.
Robust hands-on experience with AWS Glue, S3, Redshift, Athena, and Lambda, along with working knowledge of SNS, SQS, CloudWatch, EventBridge, and API Gateway.
Strong problem-solving, communication, and collaboration skills.

Nice-to-Have Skills
Experience with Amazon Kinesis or Apache Kafka for streaming data pipelines.
Exposure to Amazon MWAA or Apache Airflow for workflow orchestration.
Familiarity with AWS IAM, Lake Formation, and data governance practices.
Experience with C

📌 Aws Data Engineer Bengaluru
🏢 YMinds.AI
📍 Bengaluru