Data Engineer

Requirements: Strong experience in

Python

and

PySpark Hands-on experience of Amazon Web Services (AWS) Experience with Amazon S3

for data storage Familiarity with

Amazon CloudWatch

for monitoring Experience with

MongoDB Understanding of CI/CD pipelines Strong knowledge of data validation, transformation, and migration best practices

Responsibilities: Develop and manage

ETL pipelines using PySpark and AWS Glue . Perform

end-to-end data migration

across systems with multiple validation layers to ensure accuracy, completeness, and consistency. Design and implement

data migration strategies

tailored to business requirements. Collaborate with backend engineering teams to ensure smooth data integration during application transitions. Monitor and optimize data workflows using AWS services.