Job Summary
The Senior Software Engineer will design, develop, and support scalable cloud-native applications and data platforms using AWS, distributed systems, microservices, big data technologies, and modern data architectures. The role requires strong backend programming skills in Python and Java, hands-on experience with Kubernetes, and the ability to build reliable, high-performance cloud solutions.

Key Responsibilities
• Design, develop, and maintain scalable cloud-native applications and data platforms on AWS.
• Build and integrate solutions using AWS services including S3, Lambda, API Gateway, and EventBridge.
• Design and implement microservices-based architectures for scalable and resilient applications.
• Develop and maintain REST APIs and event-driven architectures.
• Design and implement large-scale data processing pipelines using Apache Spark and PySpark.
• Develop solutions for processing and transforming large volumes of data.
• Build and maintain data lakes, data warehouses, and modern lakehouse architectures.
• Implement and support Delta Lake or similar modern data platform technologies.
• Develop backend services and applications using Python and Java.
• Design and optimize distributed systems for scalability, performance, reliability, and availability.
• Containerize applications and deploy, manage, and troubleshoot workloads using Kubernetes.
• Collaborate with engineering and data teams to develop scalable and reliable cloud solutions.
• Troubleshoot application, data processing, infrastructure, and distributed system issues.
• Apply software engineering best practices across development, testing, deployment, and production support.

Required Qualifications
• Strong hands-on experience with AWS cloud-native engineering.
• Experience with AWS S3, Lambda, API Gateway, and EventBridge.
• Experience building scalable cloud data platforms.
• Strong experience designing and developing microservices architectures.
• Strong experience developing REST APIs and event-driven applications.
• Hands-on experience with Apache Spark and PySpark.
• Experience developing large-scale data processing pipelines.
• Strong backend programming experience with Python and Java.
• Experience with data lakes, data warehousing, and modern lakehouse architectures.
• Experience with Delta Lake or similar lakehouse technologies.
• Strong hands-on experience with Kubernetes; Kubernetes is critical for this role.
• Experience with containerized application development and deployment.
• Strong understanding of distributed systems, scalability, performance, and reliability.