Description

Job Responsibilities include:

Design, develop, and lead the implementation of scalable data engineering solutions, real-time streaming pipelines, and distributed data processing frameworks.

Build and optimize data pipelines using Python, PySpark, AWS Lambda, AWS Glue, S3, Kinesis, Apache Flink, and Confluent Kafka.

Architect and support large-scale cloud-based data platforms, ensuring high performance, reliability, scalability, and cost optimization.

Develop and tune complex SQL queries, data models, and data integration processes to support analytics and business reporting needs.

Establish engineering best practices, conduct code reviews, mentor team members, and provide technical leadership across data engineering initiatives.

Implement monitoring, automation, data governance, security controls, and operational support processes to ensure reliable production data pipelines.

Required Qualifications:

Bachelor’s degree in computer science, Information Technology, Data Engineering, Software Engineering, or a related field.

10+ years of experience in Data Engineering, Big Data, and cloud-based data platform development.

Strong hands-on experience with Python, PySpark, AWS Lambda, AWS Glue, S3, Kinesis, Apache Flink, Confluent Kafka, and advanced SQL.

Proven expertise in designing scalable data architectures, real-time streaming pipelines, distributed data processing systems, and AWS cloud-based solutions

Key Skills

Education

Any Graduate