We are looking for a skilled Data Engineer with hands-on experience in Python, PySpark, and ETL pipeline development. The ideal candidate will be responsible for building and maintaining scalable data pipelines, processing large datasets, and implementing DevOps and CI/CD practices to ensure productive and reliable data delivery.

Roles & Responsibilities
Design, develop, and maintain scalable data pipelines using Python and PySpark.
Build, optimize, and manage ETL pipelines for data ingestion, transformation, and processing.
Develop effective data processing solutions to handle large volumes of data.
Ensure data quality, pipeline performance, reliability, and scalability.
Implement and maintain CI/CD pipelines to automate code integration, testing, and deployment.




Follow DevOps best practices for deployment, monitoring, and pipeline maintenance.
Collaborate with cross-functional teams to deliver robust data engineering solutions.

Requirements
Strong hands-on experience in Python programming.
Proficiency in PySpark and distributed data processing.
Solid experience in Data Engineering and data pipeline development.
Hands-on experience in designing and implementing ETL pipelines.
Experience with DevOps practices and CI/CD pipelines.
Solid problem-solving and analytical skills.
Ability to work collaboratively in a team environment.

📌 Data Engineer Noida (India)
🏢 IRIS SOFTWARE
📍 India