AWS Data Engineer
Summary
An experienced data engineer (6-12 years) who designs, builds, and maintains scalable data pipelines, ETL/ELT processes, data lakes, and warehouses on AWS, while ensuring data quality, governance, and performance. Core technologies include AWS Glue, EMR, Lambda, S3, Redshift, Athena, Kinesis, SQL, and Python/PySpark/Scala.
Job Description
AWS Data Engineer Experience: 6-12 Years Location: Mumbai Role Overview We are looking for an experienced AWS Data Engineer to design, develop, and maintain scalable data pipelines and cloud-based data solutions on AWS. The ideal candidate should have hands-on experience in data engineering, ETL development, AWS data services, and large-scale data processing. Key Responsibilities Design, build, and maintain scalable data pipelines on AWS. Develop and optimize ETL/ELT processes for structured and unstructured data. Work with large datasets using cloud-native AWS services. Build and maintain data lakes and data warehouses. Ensure data quality, governance, security, and performance optimization. Collaborate with business stakeholders, analysts, and data scientists. Troubleshoot and resolve data pipeline and production issues. Required Skills Strong experience in AWS Cloud Services . Hands-on experience with AWS Glue, EMR, Lambda, S3, Redshift, Athena, Kinesis . Strong SQL and database expertise. Experience with Python, PySpark, or Scala. Knowledge of ETL/Data Warehousing concepts. Experience with CI/CD, Git, and DevOps practices. Understanding of data modeling and performance tuning. Preferred Skills Experience with Apache Spark, Hadoop ecosystem. Knowledge of Airflow or workflow orchestration tools. Exposure to Snowflake or Databricks. AWS Certification is an added advantage.