AWS Data Engineer

To be successful as an AWS Data Engineer you should have experience with: -

• Firsthand Experience in developing, testing and maintaining applications on AWS Cloud.

• Strong hands‑on experience with the AWS Data Analytics stack (Amazon S3, AWS Glue, Athena, Lambda, IAM, Lake Formation, KMS, STS, and Step Functions), with a proven ability to build, test, and support secure, scalable, and well‑governed data pipelines.

• Firsthand experience in Airflow and PySpark and strong knowledge of Python.

• Design and implement scalable and efficient data transformation/storage solutions using Snowflake.

• Experience in Data ingestion to Snowflake for different storage format such Parquet, Iceberg, JSON, CSV etc.

• Experience in using DBT (Data Build Tool) with snowflake for ELT pipeline development.

• Experience in Writing advanced SQL and PL SQL programs.

• Experience in AWS data pipeline development.

• HandsOn Experience for building reusable components using Snowflake and AWS Tools/Technology.

• Must have completed two major projects.

• Exposure to data governance or lineage tools such as Immuta and Alation is added advantage.

• Experience in using Orchestration tools such as Apache Airflow or Snowflake Tasks is added advantage.

• Knowledge on Ab Initio ETL tool is a plus.

• Hands on experience in Unix scripting is a plus.

  • Automation based on tools like selenium, java is a plus.