Experience Range : 7- 12 Years

Responsibilities:

• Design, implement and maintain scalable ETL jobs and data pipelines for processing and analyzing large data sets
• Build warehouses, datalakes and integrations with CRMs and analytics tools.
• Build and maintain data pipelines using Python for data extraction, transformation and loading (ETL) workflows.
• Ensure high performance, scalability, and security of applications.
• Optimize and refactor existing code for improved efficiency and maintainability.
• Write efficient, reusable, and testable code following best practices and coding standards.
• Monitor, troubleshoot and improve data workflows and pipeline performance.

Requirements:

• Proven experience as a Data Engineer or similar role.
• Deep expertise in Python for creating, automating, and optimizing ETL jobs and data pipelines.
• Strong experience with AWS services related to data engineering such as Glue, S3, Athena, Lambda, Kinesis, MSK, EventBridge, etc.
• Good understanding of backend development, RESTful APIs
• Experience with containerization and orchestration tools.
• Proficiency in database management (e.g., SQL, ORM techniques).
• Experience in software development methodologies like Agile/Scrum.
• Excellent problem-solving skills and attention to detail.
• Good to have - Knowledge on Python web frameworks such as Flask, FastAPI or Django