Description

You will design, implement, and maintain scalable data architectures and ETL pipelines on AWS using PySpark.

This role is hybrid.

Responsibilities

• Design and maintain scalable data architectures using AWS cloud services.
• Develop ETL processes using PySpark to extract, transform, and load data.
• Utilize S3, Glue, and Redshift for data storage, processing, and analytics.
• Collaborate with cross-functional teams to ensure seamless data flow across AWS services.
• Write high-quality code following data engineering and cloud deployment best practices.

Required Skills

• 5–8 years of experience in Data Engineering.
• Strong hands-on experience with PySpark for ETL and data processing.
• Proven experience with AWS data services including S3, Glue, and Redshift.
• Solid understanding of SQL, data modeling, and database design.
• Experience building and designing data pipelines on AWS.
• Proficiency with AWS Cloud infrastructure.
• Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.

Preferred Skills

• Knowledge of Airflow, Terraform, or other orchestration and IaC tools.
• Experience with real-time data processing using Kinesis or Kafka.
• Familiarity with DevOps practices, data governance, security, and compliance frameworks.

Key Skills

Education

Any Graduate