Himanshu Khatri

CEO

Pune, Maharashtra, India7 yrs 5 mos experience

Highly StableAI Enabled

Key Highlights

Expert in architecting cloud-native Data & AI platforms.
Led modernization of legacy systems for Fortune 500 companies.
Recognized for developing innovative data solutions in healthcare.

Stackforce AI infers this person is a Healthcare Data Architect specializing in cloud-native solutions and AI integration.

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Skills

Core Skills

SnowflakeGovernanceData LakehouseDatabricksCloud-native PlatformsData EngineeringData PipelinesGraph DatabasesStatistical Modeling

Other Skills

Asset DevelopmentPOCsApplied ResearchAWSTechnical DiscussionsPre-Sales Technical ConsultingBusiness Case PreparationBusiness RequirementsAzure Data LakeData ProductsGen AIOracleGlueData LakesData Models

About

Himanshu is a Solutions Architect with 8 years of experience designing cloud-native Data & AI platforms for large, regulated organizations. Himanshu work at the intersection of enterprise architecture, data platforms, and AI, helping Fortune 500 pharmaceutical companies simplify and migrate complex legacy systems into scalable, secure, production and AI ready solutions. Experience includes: 1. Architecting an Enterprise-scale cloud data solution on Azure & AWS 2. Desiging a Scalable Modern data platforms using Databricks and Snowflake 3. Enabling AI/ML and advanced analytics on governed data foundations 4. Driving architecture strategy, governance, and platform standardization at enterprise scale 5. Translating business problems into practical, scalable technical solutions Currently, focusing on building AI-ready data ecosystems that deliver real business outcomes.

Experience

7 yrs 5 mos

Total Experience

7 yrs 5 mos

Average Tenure

7 yrs 5 mos

Current Experience

Zs

5 roles

Enterprise Solutions Architect

Promoted

Jan 2026 – Present · 4 mos

Leading Snowflake Centre of Excellence (SnowCoE), owning standards, governance, Asset development, POCs, and applied research to scale Snowflake adoption across analytics and AI use cases across multiple clients in life science Industry

SnowflakeGovernanceAsset DevelopmentPOCsApplied Research

Engineering Lead

Promoted

Jul 2023 – Dec 2025 · 2 yrs 5 mos

Owned the technical strategy and architecture for a cloud-based Data Lakehouse on AWS and Snowflake, enabling scalable analytics and data-driven decision making. Engineered comprehensive data lake solutions, integrating alation to enforce robust governance and compliance.
Led the modernization of a Fortune 500 pharmaceutical legacy system by migrating from an Oracle monolith to a modern Databricks based solution , significantly boosting performance and reducing operational costs.
Actively involved in pre-sales initiatives, technical discussions, and proof of concepts that accelerated Cloud-native Platform ( like Databricks & Snowflake) adoption and transformed client data platforms.
Collaborated with C-level executives, data architects, and engineering teams to define and implement forward-thinking data strategies, seamless integration, and security best practices.

AWSSnowflakeData LakehouseTechnical DiscussionsPre-Sales Technical ConsultingBusiness Case Preparation+5

Engineering Specialist

Jan 2022 – Jun 2023 · 1 yr 5 mos

Executed a knowledge graph layer for a modernization project for a Fortune 500 pharma client by pinpointing critical data silos and areas for enhanced insight.
Designed and implemented scalable data pipelines using AWS (Glue ETL) to integrate and transform diverse pharma datasets.
Built a robust knowledge graph using AWS Neptune, SPARQL, and GraphQL, and incorporated semantic search to improve data retrieval and analytics.
Delivered tailored PoCs and interactive demos that showcased the end-to-end solution, driving stakeholder alignment and accelerating technology adoption in RWD Domain

AWSGlueData PipelinesData LakesData ModelsSemantic Search+3

Senior Engineer

Promoted

Jul 2020 – Dec 2021 · 1 yr 5 mos

Designed near-real time patient enrollment analytics platform in AWS, improving clinical trial planning efficiency by 25%
Developed data pipelines on AWS to support a web application, enabling seamless data integration. Deployed statistical models on SageMaker Inference endpoints, allowing users to trigger multiple enrollment prediction scenarios directly from the web app.
Optimized data lake ingestion & processing, enabling seamless biostatistical analysis and trial optimization.
Worked closely with biostatisticians & domain experts to build predictive models for clinical outcomes

AWSData PipelinesAWS SageMakerStatistical ModelingData EngineeringClinical Trials+1

Business Technology Analyst

Aug 2018 – Jun 2020 · 1 yr 10 mos

Developed a first-of-its-kind data-driven site selection platform for clinical trials, improving selection accuracy and efficiency.
Built data ingestion pipelines using ZS Proprietary Data Management Framework (on AWS), standardizing clinical trial datasets from multiple sources
Designed microservices architecture to support scalable data APIs & visualization for a web-based application
Developed flask services for the web-based application and deployed the same in AWS EKS
Recognized as Project Champion (2019) for delivering an industry-first data integration platform.

Bmc software

Research Intern

Jul 2017 – May 2018 · 10 mos · Pune Area, India

As an intern, I developed a cloud automation plugin using the Jenkins platform which significantly reduced the shipping time of software by automating the testing process. This plugin was integrated into the BMC automation framework and was able to improve software delivery by reducing the time spent on testing. My experience as an intern provided me an opportunity to learn and work with the latest technology in software development and automation.