Data Engineer - AWS (8-10 yrs)

We are looking for an experienced AWS Data Engineer to design, develop, and optimize scalable data pipelines and ETL workflows using cloud technologies.

The ideal candidate will have expertise in Python, SQL, Kafka, and AWS services such as S3, Redshift, Glue, and Lambda. This role requires strong problem-solving skills, the ability to collaborate with global teams, and a passion for building high-performance data solutions.

Roles and Responsibilities :

- Design and implement ETL workflows to process and transform large datasets efficiently.

- Develop and maintain scalable data pipelines using AWS services like S3, Redshift, Glue, and Lambda.

- Write efficient Python and SQL scripts for data integration, transformation, and analytics.

- Utilize Kafka for real-time data streaming and event-driven architecture.

- Ensure data integrity, security, and compliance with industry best practices.

- Optimize data architecture for high availability, performance, and scalability.

- Collaborate with cross-functional teams to understand business requirements and provide data-driven solutions.

- Troubleshoot and resolve performance bottlenecks in large-scale data workflows.

- Provide technical leadership and mentor junior data engineers.

- Work with offshore teams and be flexible to collaborate across UK and US time zones.

- Skills and Qualifications Required

Must-Have :

- Strong expertise in ETL workflows and data engineering.

- Proficiency in Python, SQL, and Kafka for data processing and integration.

- Hands-on experience with AWS ecosystem including S3, Redshift, Glue, and Lambda.

- Experience in data modeling, data warehousing, and real-time data processing.

- Excellent problem-solving and troubleshooting skills in large-scale data environments.

Good-to-Have :

- Knowledge of Oracle Cloud Infrastructure (OCI).

- Experience with CI/CD pipelines for data engineering.

- Familiarity with DevOps and Infrastructure as Code (IaC) tools