Krunal T.

About Krunal T.

Walmart Global Tech leverages my expertise in developing scalable streaming applications, enabling real-time data processing with high availability and low latency. Collaborating with cross-functional teams, we designed robust systems to handle large-scale data ingestion and consumption. Key contributions include enhancing deployment pipelines with Apache Airflow and building a streaming pipeline with Apache Spark capable of processing transactions per minute. These efforts empower downstream customers with actionable insights in Google BigQuery within a 15-minute latency window. With over two years of experience in cutting-edge data engineering roles, I am committed to creating innovative solutions that optimize system reliability and performance. My technical proficiencies in Node.js, Linux, and Java, paired with a passion for tackling complex challenges, drive impactful results. At Walmart Global Tech, I focus on delivering data-driven strategies that empower global operations and enhance decision-making capabilities.

Experience

1. Software Engineer

   Walmart Global Tech

   Nov 2022 — Present · Sunnyvale, CA, US

   Developed streaming applications that is facilitating real time data from various global stores with high availability and low latency. • Designed a comprehensive system for the consumption of data from end to end. Ensured the system had the capacity to receive all the files and process them efficiently, regardless of the large volume of data. • Enhanced the deployment pipeline by integrating with Apache Airflow, automating workflows and improving system reliability.• Designing and implementing Streaming pipeline with Apache Spark, ingesting transactions at 200K Transactions Per Minute. This pipeline provides data to downstream customers in Google BigQuery with latency of 15 minutes• Led Holiday Readiness planning to ensure system stability and scalability during peak load, enabling applications to handle holiday retail surges seamlessly.• Developed end-to-end processing for AutoLinking transactions, including ingestion, opt-in validation, and deletion handling across BigQuery, Cassandra, Kafka, and Elasticsearch for accurate and traceable purchase history page.• Designed and implemented a high-performance API using Spring to link and auto-link transactions with customer IDs, achieving p99 of sub-100ms latency• Designed and developed a high-availability Customer Transaction History API using Spring and Cassandra, enabling multiple teams—including Returns—to retrieve customer transactions in under 50 ms with a sustained rate of 150 RPS (m1_rate).• Built a sub-500 ms system for matching in-store receipts with dotcom accounts using payment card tokens, integrating eReceipts, Customer Choice, and Customer Transaction history data via Kafka, Spring, and Cassandra, with support for real-time onboarding and preference-based linkage logic.

Education

• Santa Clara University

  Master of Science - MS, Computer Science

  2017 — 2019

• Gujarat Technological University (GTU)

  Bachelor's degree, Computer Science

  2010 — 2014

Skills

• C
• Microsoft Office
• Microsoft Excel
• Microsoft Word
• Microsoft Powerpoint
• Git
• C++
• Cascading Style Sheets (Css)
• Docker
• Amazon Ec2
• Javascript
• Html
• Sql
• Linux
• Java
• Amazon Web Services (Aws)