Java Full Stack and Data Engineering

Data Engineering Design and develop data pipelines for batch and real-time processing. Build ETL/ELT solutions to support analytics and business intelligence initiatives. Process and transform large datasets using Spark/PySpark. Work with data warehouses and cloud-based data platforms. Support data integration, governance, and quality initiatives. Cloud & DevOps Develop and deploy applications on AWS, Azure, or GCP. Implement CI/CD pipelines and automation practices. Leverage Docker and Kubernetes for containerized deployments

Application Development Design, develop, and maintain enterprise-grade applications using Java and modern Full Stack technologies. Build scalable microservices and RESTful APIs using Spring Boot. Develop secure, high-performance, and resilient applications. Participate in architecture, design, and code review sessions. Full Stack Development Develop responsive, intuitive, and user-friendly web applications using React.js or Angular. Collaborate with UX/UI teams to implement modern user experiences. Build reusable frontend components and frameworks.

Technical Leadership Mentor junior and mid-level engineers. Conduct code reviews and enforce engineering best practices. Drive technical discussions and contribute to architecture decisions. Lead feature delivery and support resolution of production issues. Promote innovation, continuous improvement, and engineering excellence.