➣ Working as part of NextGen BigData R&D Team.

Amdocs Technology (R&D) :➣ Contributed to Amdocs AI and Data Platform Team.➣ Developed data collection components to acquire batch and real-time data seamlessly from diverse sources such as Oracle, Kafka, MySQL, and file systems.➣ Implemented an autoscaling mechanism using Kubernetes Horizontal Pod Autoscaler (HPA) based on Kafka consumer lag, tracked through Prometheus.➣ Created Airflow workflows for managing Spark applications on Kubernetes, including the development of custom sensors to meet specific job requirements.➣ Designed and implemented a Kafka error handling framework, covering both consumer and producer error scenarios.➣ Translated high-level system requirements (HLS) into detailed, actionable technical solutions.➣ Conducted Proof of Concepts (PoCs) to validate and improve new technologies and approaches.➣ Ensured high code quality through JUnit tests, component testing, and regular codebase refactoring, along with in-depth code reviews and static analysis.

Amdocs Data & Intelligence :➣ Created a Reconciliation framework leveraging Amdocs Data Hub, integrating multiple Pyspark jobs and orchestrating their scheduling with Airflow.➣ Optimized Spark Jobs for enhanced performance and fault prevention.➣ Accountable for upholding the Real-Time data pipeline in the Production environment, promptly addressing and rectifying any raised issues.➣ Successfully transitioned HQL scripts to Spark Scala using SBT.➣ Collaborated with various clients, including Telstra, XLCOM, and 3IR, to deliver tailored solutions.