Description

You will build and maintain data pipelines using AWS services.

This role is hybrid.

Responsibilities

• Design and implement ETL processes using AWS Glue and EMR.
• Manage and optimize data workflows using Kafka and Airflow (MWAA).
• Develop data solutions using Python, integrating with S3, Redshift, and DMS.
• Tune SQL queries and optimize existing ETL jobs for performance.

Required Skills

• 4 to 8 years of professional experience in data engineering.
• Proficiency in Python (preferred), Java, or Scala.
• Hands-on experience with AWS services: S3, Glue, EMR, Redshift, SNS, SQS, DMS, MWAA.
• Experience with Infrastructure as Code using Terraform.
• Strong understanding of SQL tuning and ETL optimization techniques.
• Familiarity with streaming tools such as Kafka and Kinesis.
• Experience with monitoring tools like Splunk or CloudWatch.

Preferred Skills

• Experience with large-scale distributed data systems.
• Knowledge of data modeling best practices.

Key Skills

Education

Not specified