About

Jay Bodra is a dynamic and collaborative Data Engineer with over 7 years of relevant experience in designing, developing, and testing reliable solutions for intricate business problems involving Enterprise Data Warehouse systems, Real-time analytics, Big data, and Reporting. He has a proven track record of using the right tools for building intuitive and scaling architecture to help the organization efficiently process and analyze the enormous amount of structured and unstructured data. Currently, Jay is working as a Data Engineering Manager at Keller Williams Realty, Inc. where he has been responsible for architecture and developing core data platform components, designing and building various microservices to enhance existing data, and supporting streaming workloads. He has also developed a core monitoring system utilized in different data pipelines using API or message bus architecture, designed architecture and process to handle data change management for different data pipelines, and built cross-functional relationships with Data Scientists, Product Managers, and Software Engineers to understand and deliver data needs. Additionally, Jay has coached, developed, and mentored a team of collaborative data engineers and created and evangelized best practices for unit testing, CI/CD, DevOps, performance testing, capacity planning, documentation, monitoring, alerting, and incident response. In the past, Jay has worked in different roles at Keller Williams Realty, Inc., including Senior Data Engineer and Data Engineer. In these roles, he has designed and developed a streaming pipeline to move huge volumes of real estate listing data across their consumer-facing application in near real-time to meet the industry service-level agreements. He has also created architecture to standardize, maintain, and support 480 heterogeneous data sources, designed automation for importing and supporting geospatial datasets, and worked with machine learning team to build a model to attribute data to an associate. Jay holds a Master’s Degree in Computer Science from the University of Texas and a Bachelor's Degree in Computer Engineering from NMIMS. He is proficient in Data Engineering, Senior Software Engineering, ETL, testing, Data Warehouse, CI/CD, Big Data, Microservices, DevOps, ML, SQL, Elastic Search, AI, MongoDB, and other relevant technologies.