- Excellent system design skills for designing distributed systems with
scalability, resiliency, security, and performance best practices.
- Advanced proficiency in Java (17/21+) and Spring Boot for building scalable
RESTful microservices. Strong command of Kafka for event-driven architectures, including topic design, partitions, consumer groups, and delivery semantics.
- Strong experience in Java (Strong hands-on coding expertise), Spring Boot /
Spring Framework, AWS Cloud and Kafka (Deep expertise in event streaming and messaging)
- In-depth knowledge of Cassandra for distributed data modeling, partition
strategy, and query tuning at scale.
- Extensive experience with AWS data lake & ETL technologies (S3, Glue, EMR,
Lambda, Step Functions) and Maven for build/dependency management.
- Solid expertise in containerization and orchestration using Docker and
Kubernetes, deploying workloads on AWS EKS and ECS.
- Hands-on mastery of Apache Spark (batch + streaming) for large-scale data
processing and performance optimization.Proven capability in Jenkins-based CI/CD automation, including pipelines, quality gates, artifact publishing, and deployments.
- Effective AI utilization to boost development productivity by leveraging AI
agents/skills for coding assistance, test generation, refactoring, documentation, and faster troubleshooting.
- Demonstrated experience leading effective use of approved AI-assisted
software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
- Strong understanding of responsible AI use in engineering workflows,
including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices