Description

Job Responsibilities include:

Architect, design, and implement scalable batch and real-time data pipelines using AWS services and event-driven frameworks.

Develop and optimize ETL/ELT workflows using Python and PySpark for high-performance data processing.

Build and manage data lakes and warehouses using S3, Glue, Redshift, and Athena for analytics and reporting needs.

Ensure data quality, security, governance, and monitoring using tools like CloudWatch and best practices in cloud environments.

Lead technical design reviews, mentor engineering teams, and enforce best practices in architecture and coding standards.

Implement CI/CD pipelines, automation frameworks, and infrastructure-as-code solutions to streamline deployments and operations.

Required Qualifications:

Bachelor’s degree in computer science, Engineering, or a related field.

15+ years of experience in software engineering, with strong focus on AWS and data engineering.

Deep expertise in AWS services, event-driven architecture, and large-scale data pipeline development using Python/PySpark.

Strong understanding of distributed systems, CI/CD, data security, and ability to lead architecture design and mentor teams

Key Skills

Education

Any Graduate