Description

You will design, build, and maintain scalable data pipelines on AWS using Python, PySpark, and serverless technologies.

This role is on-site.

Responsibilities

• Develop and optimize ETL workflows using AWS Glue, Lambda, and PySpark for large-scale data processing.
• Implement real-time data streaming solutions using Kafka, Kinesis, and Apache Flink.
• Ensure data quality, reliability, and performance across distributed AWS services.
• Collaborate with stakeholders to define data requirements and deliver robust data products.

Required Skills

• 5+ years of professional experience in data engineering or related fields.
• Strong proficiency in Python and PySpark for data manipulation and analysis.
• Hands-on experience with AWS services: Glue, Lambda, Kinesis, and EC2/S3.
• Experience with stream processing frameworks like Kafka and Apache Flink.
• Bachelor's degree in Computer Science, Engineering, or a related technical field.
• Deep understanding of ETL best practices, data modeling, and distributed systems.

Key Skills

Education

Bachelor's degree