San Jose, California, United States
Hello, thank you for visiting my profile! I’m a backend focused software engineer specializing in data engineering, with over 5 years of experience building scalable, production grade data ingestion solutions, platforms, and backend systems in the cloud. My expertise lies in streaming ingestion systems, infrastructure-as-code (IaC) deployment of data pipelines, OpenTelemetry, and cloud-native service development. I’m passionate about designing robust, maintainable data management systems that help customers reliably move and monitor data at scale. At Splunk, I played a key role in building the foundation of Splunk Cloud Data Manager across AWS ecosystem, leveraging infrastructure-as-code deployments and native cloud services to ingest logs, events, and metadata into Splunk. I also contributed to developing Splunk Cloud Platform components such as the Splunk Edge Processor and the next generation Splunk Search Processing Language (SPL2), deepening my expertise in data stream processing. Currently, I’m part of a brand new team bringing up a multi-tenant cloud service that will enable API driven automation for essential data management workflows empowering both customers and AI agents to manage data more efficiently. If you’re curious to learn more about my work, feel free to explore the Experience section of my profile!
Splunk Cloud Data Management, Unified API Service * Joined the team from its inception, contributing to the development of a brand-new multi-tenant service in the Splunk Cloud Platform. * Collaborating with cloud service teams and platform architects to design a unified API platform that provides frontend applications, Splunk administrators, and AI agents with a standardized data model and seamless integration capabilities. * Designing state-changing APIs to support automated workflows and end-to-end orchestration of data management operations. * Driving standardization of Data Management APIs across cloud services within the Data Management organization to improve consistency, reusability, and integration. * Technologies used: Golang, Docker, Kubernetes, and AWS.
Splunk Cloud Data Management, Content Engineering for Edge Processor and Search Processing Language, version 2 (SPL2) • Collaborated cross-functionally with teams across the Data Management organization, including Splunk Edge Processor, Ingest Processor, SPL2 Language, Data Orchestration, and UI/UX to design and implement built-in SPL2 functions and data processing content features. • Developed SPL2 stream functions within the stream processor of edge/ingest processors and SPL2 compiler, bridging gaps between SPL and SPL2 to expand the capabilities of cloud-native ingestion pipelines, enabling source-type-based partitioning, and accelerating customer adoption of SPL2. • Designed and led the development and release of a feature that syncs data processing content between Splunk Enterprise Cloud and on-prem instances with the Splunk Edge Processor, delivering a 25% reduction in time to value and a more seamless customer experience. • Served as Scrum Master for over a year, partnering with tech leads, EMs, and PMs to plan and drive the delivery of key product features. • Technologies used: Golang, OpenTelemetry, Docker, Kubernetes, and AWS.
Splunk Cloud Data Manager • Joined the team from its inception, contributing to the development of a new cloud-native data ingestion product for Splunk Cloud, which helps to reduce customers' time to value; cutting data ingestion setup time from days or weeks to just a few hours for supported AWS, Azure, and GCP data sources. • Designed and implemented backend APIs that integrate with both AWS and Azure to manage data input configurations for cloud-native data sources. • Developed data pipelines using AWS services (IAM, CloudWatch Logs, EventBridge, Kinesis Data Firehose, Lambda, S3, SQS, and more) to send logs, events, and metadata to Splunk Cloud instances, and built APIs that dynamically generate infrastructure-as-code (IaC) deployment templates. • Improved engineering productivity by developing a platform provisioning automation tool to perform prerequisite checks and handle automated resource provisioning and deprovisioning across dev and prod environments; reducing setup time by 70%, with over 2,000 successful provisions to date. • Led planning and implementation of new data source integrations and backend capabilities; scaling support to 12+ data sources. • Enhanced product observability by implementing telemetry, standardizing application logs, and creating health dashboards to monitor SLIs and support root cause analysis; reducing issue detection time by 75% and average root cause identification time by 60%. • Collaborated cross-functionally with platform, frontend, and product management teams to design, implement, and deliver key features across the stack. • Gained end-to-end product lifecycle experience through PI planning, design, beta releases, public/private previews, limited availability, and GA launches. • Completed Scrum Master training and served as Scrum Master for the team. • Technologies used: Python, AWS, and Azure.
• Collaborated with the SAP Service Cloud team to integrate Cloud for Customer (C4C) and Field Service Management (FSM) systems. • Developed a microservice API endpoint for efficient file upload/download using AWS S3, enhancing user experience. • Optimized memory utilization for the API, resulting in faster processing times and improved performance. • Worked with the UI/UX team to transform a prototype into a production-ready Angular component.
• Assisted in the Intensive Foundations of Computer Science course (CS5001) at Northeastern University. • Provided personalized guidance and support to students, enhancing their understanding of complex concepts. • Conducted regular office hours, fostering a supportive learning environment and improving student performance.
• Developed a document approval web application that streamlined processes for three engineering departments, reducing manual work by 30%. • Deployed the application on an on-premise Linux server (RHEL). • Collaborated with stakeholders to gather requirements, enhancing user experience and satisfaction. • Technologies used: Angular, Bootstrap, Express.js, Node.js, Passport.js, CryptoJS, and MySQL.
• Standardized the production capacity assessment process and successfully established a reliable KPI, actual production capacity • Collaborated with multi-tier suppliers to implement new standards and drive continuous improvement initiatives to optimize the production capacity • Streamlined the production capacity monitoring process and reduced the production capacity assessment time by 25% • Analyzed past sales and inventory data, applied regression analysis, and produced inventory projection models to improve inventory management