AWS Data Engineer

The AWS Data Engineer will design, develop, and maintain scalable data engineering solutions on AWS. You will build and optimize ETL/ELT pipelines for data ingestion and transformation, and partner with BI, AI/ML, and infrastructure teams to deliver a reliable data platform. The role is based in Bengaluru and follows a work-from-office model.

Our client is a leading global software and technology services provider serving enterprises across multiple industries. They are known for building data-driven solutions at scale and for a collaborative, fast-paced culture that values innovation and continuous learning.

Responsibilities

• Design, develop, and optimize scalable ETL/ELT pipelines for data ingestion and transformation.
• Build and maintain robust data pipelines using AWS cloud services.
• Partner with BI, AI/ML, and infrastructure teams to deliver reliable and scalable data platform solutions.
• Develop efficient SQL queries and Python scripts for data processing, automation, and analytics.
• Create and maintain technical documentation, including solution designs, data flow diagrams, and operational guides.
• Write comprehensive unit tests and perform code reviews to ensure high-quality, maintainable code.
• Monitor, troubleshoot, and optimize data pipelines for performance, scalability, and reliability.
• Follow coding standards, best practices, and data governance guidelines.

Requirements

• 3-5 years of hands-on experience in data engineering, with strong ETL/ELT pipeline design and development.
• Proficiency in SQL and Python programming.
• Hands-on experience with AWS services including Amazon Redshift, AWS Lambda, Amazon S3, AWS IAM, and Amazon CloudWatch; AWS Glue is preferred.
• Understanding of data warehousing concepts and dimensional data modeling.
• Experience with version control (Git), unit testing, and software development best practices.
• Experience with workflow orchestration tools such as Apache Airflow (preferred).
• Strong analytical, problem-solving, and debugging skills with excellent communication and documentation abilities.
• Bachelor's degree in Computer Science, Software Engineering, MIS, or equivalent combination of education and experience.

Skills

ETL/ELT pipeline development, SQL, Python, Amazon Redshift, AWS Lambda, Amazon S3, AWS IAM, Amazon CloudWatch, AWS Glue, Apache Airflow, Data warehousing and dimensional data modeling, Git, Unit testing, CI/CD and DevOps practices, Spark, PySpark, or Databricks, AI/ML data pipelines and feature engineering, Agile/Scrum