Jay J. Email & Phone Number

Austin, Texas, Us

• Directed a cross-functional team in the full migration project at Johnson & Johnson, overseeing the seamless transition of data infrastructure and applications.• Spearheaded the development of data processing pipelines utilizing Spark and Flink technologies, achieving a remarkable 30% reduction in processing time for real-time analytics of health cases data.• Implemented RESTful APIs to facilitate integration with internal CRM systems, resulting in a notable 20% decrease in data synchronization errors. Adopted GraphQL to enhance data querying capabilities and facilitate smoother data exchange.• Orchestrated the deployment of containerized microservices using Docker and Kubernetes, streamlining deployment processes and reducing deployment time by 40%. This initiative significantly improved system scalability and flexibility.• Integrated Kenvue's proprietary genAI solution into the data processing pipelines, leveraging advanced machine learning algorithms to enhance data analysis and decision-making processes.• Employed optimization techniques to enhance PostgreSQL database queries, yielding a substantial 25% improvement in query performance tailored specifically for managing health cases data. Leveraged SQL expertise for fine-tuning database operations.

Seattle, Wa, Us

• Architected and implemented a serverless data processing solution utilizing AWS Lambda and Amazon EMR for a healthcare client, resulting in a significant reduction of infrastructure costs by 50%.• Successfully deployed and maintained RESTful APIs for a client, ensuring an impressive uptime of 99.99% and seamless integration with partner systems.• Orchestrated the deployment of Dockerized microservices on AWS ECS, leading to a 60% increase in deployment frequency and a reduction in downtime during deployments, thereby enhancing system reliability and efficiency.• Played a key role in leading the migration of a large-scale platform from on-premises data centers to AWS cloud infrastructure, leveraging hybrid cloud solutions with Azure for seamless transition and scalability.

Bangalore, Karnataka, In

Technology Analyst (Data Engineer & ML Specialist)- Full Time• Designed and implemented real-time document processing pipelines utilizing advanced NLP techniques and Large Language Models (LLM), handling over 1TB of unstructured data daily for PG&E, a leading provider of natural gas and electric services in northern and central California.• Managed a distributed Cassandra database cluster comprising more than 100 nodes, achieving a remarkable uptime of 99.99% and significantly reducing data replication latency by 30% to ensure seamless access to indexed documents for operational insights and customer service improvements.• Developed RESTful APIs for integrating the Intelligent Document Retrieval system with PG&E's existing infrastructure, following GraphQL standards to enable efficient querying and retrieval of relevant documents for various departments including customer service, maintenance, and regulatory compliance.• Orchestrated Kubernetes deployments for containerized machine learning models, enhancing the efficiency of document classification and retrieval by 40% through predictive maintenance applications, leveraging Azure's cloud infrastructure for scalable and reliable deployment within PG&E's data ecosystem.• Implemented CI/CD pipelines to automate the deployment and testing processes, ensuring rapid and consistent delivery of updates and improvements to the Intelligent Document Retrieval system. This streamlined approach increased development efficiency and minimized deployment errors.

Austin, Texas, Us

• Developed data processing pipelines in Python for analyzing telemetry data from Tesla Model 3 vehicles, contributing to a 15% improvement in predictive maintenance accuracy.• Leveraged GCP (Google Cloud Platform) for deploying scalable and fault-tolerant microservices to process and analyze vehicle telemetry data in real-time.• Designed and implemented RESTful APIs for accessing vehicle data from Tesla's mobile app, ensuring adherence to OpenAPI standards for seamless integration with third-party applications.• Utilized Apache Kafka for real-time streaming of vehicle sensor data, enabling Tesla to perform advanced analytics on driving patterns for optimizing vehicle performance and enhancing safety features.• Managed cloud infrastructure on GCP, ensuring efficient data storage, processing, and analysis capabilities for Tesla's vehicle telemetry data.

Los Angeles, Ca, Us

Taught diverse courses in Information Systems Programs including programming, databases, computer literacy, and software methodologies. Assisted in maintaining equipment and developing curriculum. Obtained industry certifications to teach some courses. Prepared and corrected exams and assignments, scheduled student conferences, and provided academic advisement. Contributed to departmental development, selection of course materials, and demonstrated flexibility in scheduling under the guidance of professor.

Gandhinagar, Gujarat, In

• Designed and implemented database architectures supporting over 100 enterprise-level applications, ensuring dataintegrity and optimizing performance for a user base of 500+ employees.• Administered and maintained SQL Server databases, achieving 99.9% uptime through performance tuning, regularbackups, and disaster recovery planning, which safeguarded critical business data.• Developed and optimized complex SQL queries, stored procedures, and triggers, reducing data retrieval times by 30%and improving overall system efficiency.• Managed network infrastructure, ensuring 24/7 reliable connectivity and security for over 200 network devices,including routers, switches, and firewalls, resulting in a 20% reduction in network downtime.• Automated routine database and network tasks, enhancing operational efficiency by 40% and significantly reducingmanual intervention through scripting and advanced scheduling.

Postgraduate Degree, Business Analytics

Master Of Science - Ms, Information Systems

Bachelor Of Engineering - Be, Computer Engineering