AWS Data Engineer
Posted
Summary
Designs, builds, and maintains scalable AWS data pipelines, ETL/ELT processes, data lakes, and warehouses using services like Glue, EMR, Lambda, S3, Redshift, Athena, and Kinesis. Requires strong SQL, Python/PySpark/Scala, and DevOps skills; a senior 6-12 year role based in Mumbai.
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.