Description

Key Skills: AWS, Pyspark, Python, Data Bricks, Kafka, Data Modelling, Azure Devops

Roles and Responsibilities:

• Provide support for DevOps, cloud infrastructure, and ETL/ELT data engineering activities within the project team.
• Build, maintain, and support event-driven data processing pipelines using Kafka.
• Develop API-based data ingestion and transformation workflows using REST services.
• Support downstream data modeling and data pipeline optimization activities.
• Assist in automation, scheduling, and job development for data workflows on AWS and Databricks platforms.
• Monitor and troubleshoot data pipelines to ensure reliability and performance.
• Collaborate with cross-functional teams to support scalable and secure data engineering solutions.
• Participate in GxP validation and qualification activities as required in regulated environments.
• Follow development best practices, documentation standards, and data governance processes.

Skills Required:

• Strong hands-on experience with PySpark and Python for data engineering and transformation tasks.
• Experience working with AWS cloud services and Databricks platform.
• Good understanding of Kafka and event-driven data processing architectures.
• Knowledge of data modeling concepts and ETL/ELT pipeline development.
• Experience with REST API-based data ingestion and integration workflows.
• Familiarity with DevOps practices and exposure to Azure DevOps tools.
• Understanding of cloud-based data processing, workflow orchestration, and automation concepts.
• Strong analytical, debugging, and problem-solving skills.
• Ability to work effectively in collaborative and fast-paced project environments.

Education: Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field

Key Skills

Education

Any Graduate