Jimish Jitendra Kadakia
Senior Technical Architect
Nutley, New Jersey, United States
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Jimish Jitendra Kadakia is a seasoned data and analytics professional with over a decade of experience designing and implementing strategic data transformation solutions across diverse industries. His expertise lies in cloud migration, data visualization, modern data stack tools, and business intelligence, with deep proficiency in technologies such as Snowflake, dbt, Alteryx, Tableau, Thoughtspot etc.
Currently serving as a Senior Technical Architect/Solutions Architect at Snowflake, Jimish leads enterprise-grade implementations across sectors like financial services, telecommunications, manufacturing, and fintech. He plays a pivotal role in helping organizations architect complex data solutions, aligning technical delivery with business strategy, and advising executive leadership on future-state architecture, roadmaps and execution plans.
Previously, as a Senior Consultant at Slalom, Jimish co-led the Center of Excellence for Starburst, ThoughtSpot, and dbt. He drove modernization projects using data lakes and cloud platforms, developed visualizations and architecture for cross-industry clients, and mentored consultants across multiple U.S. markets. He also led architectural and engineering efforts at a startup in travel/hospitality, a global telecom firm, and a multinational insurance company, implementing solutions ranging from Snowflake cost optimization to Databricks Medallion architecture.
From 2020 to 2022, Jimish worked at 14 West (an Agora Company) as a Sr. Business Intelligence Developer/Architect, supporting over 700 users and spearheading a large-scale ThoughtSpot cloud migration. His role emphasized business-driven analytics, data democratization, and operational efficiency through BI tools and dashboards.
His earlier experience includes analytics roles at Morgan Stanley and the National Stock Exchange of India, where he honed his expertise in business analysis, risk management, and systems integrations.
Jimish holds a Master’s in Information Systems from the University of Maryland, Baltimore County, and a Bachelor's in Information Technology from the University of Mumbai. He has also completed postgraduate certifications in Business Analytics, AI & Machine Learning, and Fintech. He continues to pursue advanced certifications, including those from AWS, Snowflake, Databricks, and ThoughtSpot.
Area of Expertise
Topics
Transforming Healthcare with AI Driven Cloud Data Platforms
Healthcare organizations are generating more data than ever before from patient records, medical imaging, connected devices, and operational systems. Yet too often this data remains siloed or delayed, limiting its potential to improve patient outcomes and operational efficiency. By combining the power of cloud platforms with AI driven data engineering, we now have the ability to deliver real time, reliable, and secure insights across the healthcare ecosystem.
In this session, I will share how I have worked with enterprises to build modern data architectures that integrate cloud scalability with AI powered automation. I will discuss how predictive monitoring and anomaly detection can proactively identify issues in data pipelines, how self healing architectures reduce downtime, and how advanced analytics can help clinicians and administrators make timely decisions. I will also highlight strategies for balancing innovation with governance, ensuring compliance while enabling faster research and improved care delivery.
Attendees will walk away with a clear understanding of how to design and implement AI enabled cloud data platforms that unlock the full potential of healthcare data while improving patient outcomes, reducing costs, and ensuring trust in every insight.
Transforming ETL with AI Driven Cloud Data Pipelines
As organizations generate more data than ever, traditional ETL workflows often slow down decision making and create fragile systems that fail to scale. By applying AI techniques to cloud native data platforms, we can now design pipelines that are self healing, reliable, and capable of delivering insights in real time.
In this session, I will share how I have helped enterprises modernize their data engineering practices using AI powered automation in the cloud. I will discuss how predictive monitoring and anomaly detection reduce downtime, how orchestration frameworks improve reliability, and how platforms like Snowflake and dbt integrate to create cost efficient architectures.
Attendees will walk away with practical strategies for rethinking ETL through AI driven cloud data pipelines that improve scalability, reduce costs, and accelerate analytics delivery.
From ETL to AI Powered Pipelines Practical Data Engineering for Developers
Many developers still spend too much time fixing broken ETL jobs and struggling with fragile data processes. Modern data engineering offers us a better way by combining cloud scale platforms with AI powered automation that makes pipelines faster, smarter, and more reliable.
In this session, I will share how I have helped teams move beyond traditional ETL and build autonomous, self healing data pipelines. I will cover how stream processing frameworks deliver real time insights, how predictive monitoring and anomaly detection prevent downtime, and how tools like Snowflake and dbt integrate into developer workflows on the cloud.
Attendees will gain practical guidance on how to design and implement resilient pipelines, reduce operational overhead, and bring AI driven intelligence into their daily development practices. This talk is designed to give developers hands on strategies that they can start applying right away in their own projects.
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