Description

You will architect and lead distributed, data-intensive application development.

This role is on-site.

Responsibilities

• Define and implement system architecture for scalable, reliable, and secure distributed applications.
• Build and optimize large-scale data pipelines using Databricks and PySpark.
• Architect and manage AWS-based solutions for compute, storage, and analytics workloads.
• Develop and maintain automated deployment workflows using CI/CD practices.
• Design and deploy machine learning models into production pipelines for batch and real-time processing.

Required Skills

• 8+ years of experience in Databricks architecture and lakehouse implementation.
• Strong proficiency in PySpark for distributed data processing and transformation.
• Deep understanding of Big Data technologies and distributed computing principles.
• Hands-on experience with AWS services for data storage, compute, and analytics.
• Experience working with Azure Data Lake and hybrid cloud data environments.
• Strong knowledge of Machine Learning workflows, model deployment, and MLOps practices.
• Proficiency in designing data models using RDBMS and NoSQL databases.
• Experience implementing CI/CD pipelines for data engineering projects.
• Familiarity with GitHub for version control and collaborative development.

Key Skills

Education

Any Graduate