Description

Responsibilities include:

Design, develop, and maintain scalable real-time and near real-time data pipelines using Apache Spark, PySpark, Flink, Kafka, and Airflow.

Extract, transform, and load data from relational and NoSQL databases, including MongoDB, into enterprise data platforms.

Build and enhance microservices and APIs using Java, Spring Boot, and Python to support data-driven applications.

Monitor, troubleshoot, and optimize data workflows to ensure high performance, reliability, and data quality.

Collaborate with cross-functional Agile teams to deliver innovative data engineering solutions and meet business requirements.

Develop unit and integration tests, maintain code quality standards, and manage source code using Git/SVN version control tools.

Required Qualifications:

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

5-10 years of experience in Data Engineering, Software Development, or Big Data technologies.

Hands-on expertise in Python, Java, Apache Spark, PySpark, Apache Flink, Kafka, and Airflow for building scalable data pipelines.

Strong experience working with MongoDB, Cassandra, and other relational/NoSQL databases in enterprise environments

Key Skills

Education

Any Graduate