Analytical Database Platform

• Implemented aggregation and write execution plan operators for pipelined and parallel runtime. Conducted performance profiling, created benchmarks, and analyzed flame graphs for performance enhancements.

• Resolved bugs in the core of a graph database, addressing issues with parallel query execution, task scheduling, caching and JIT code compilation. Collaborated on customer-reported performance concerns, conducting analysis of Java CPU and memory profiles.

• Collaborated on design of Composite Database enabling access of partitioned graphs in a distributed Cypher query; incorporated work on clustering, query parsing, planning and scheduling on top of Neo4j kernel.

• Migrated over 30 Rest API endpoints contributing to the monolith separation initiative, reducing coupling between two applications, mitigating complex updates and schema changes within the shared MongoDB database.

• Identified and resolved critical issues causing log pollution, resulting in a 90% reduction of false positive error entries. Implemented structured logging and monitoring dashboards, enhancing troubleshooting efficiency.

• Developed an application on AWS Lambda, reducing the time invested in monthly report generation by the recruitment team by 50%. Integrated email notifications to alert about candidate profiles transitioning into an inactive status.

Remote continuation of earlier work. Cake become part of DSS.

• Led the development of microservice delivering encrypted content for Android devices in a multi-DRM platform for Disney+ and television. Migrated 10k+ license keys to AWS KMS envelope encryption, integrated CI/CD workflows and system monitoring.

• Executed performance testing and scalability tuning, validating the system’s robustness to support 1M+ of concurrent users with low latency, high availability and resiliency.

• Leveraged proficiency in Scala, functional programming, AWS and Docker; conducted cross-team knowledge sharing sessions.