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Hi, I'm Piyush Khedkar, a versatile full-stack professional with experience in healthcare and SaaS. I design scalable cloud-native applications, build RESTful APIs, and deploy AI-driven solutions using Python, AWS, and Snowflake. I enjoy turning complex data into actionable insights and thrive in collaborative environments to deliver measurable outcomes for patients and customers. I specialize in end-to-end data and AI solutions—from data ingestion and governance to production-grade ML models and GenAI workflows. My passion is solving real-world problems through robust architectures, clean code, and purposeful experimentation, all while keeping security and observability at the forefront.…Hi, I'm Piyush Khedkar, a versatile full-stack professional with experience in healthcare and SaaS. I design scalable cloud-native applications, build RESTful APIs, and deploy AI-driven solutions using Python, AWS, and Snowflake. I enjoy turning complex data into actionable insights and thrive in collaborative environments to deliver measurable outcomes for patients and customers. I specialize in end-to-end data and AI solutions—from data ingestion and governance to production-grade ML models and GenAI workflows. My passion is solving real-world problems through robust architectures, clean code, and purposeful experimentation, all while keeping security and observability at the forefront.

Piyush Khedkar

AI Engineer, Data Scientist, Full Stack Developer, +4

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Hi, I'm Piyush Khedkar, a versatile full-stack professional with experience in healthcare and SaaS. I design scalable cloud-native applications, build RESTful APIs, and deploy AI-driven solutions using Python, AWS, and Snowflake. I enjoy turning complex data into actionable insights and thrive in collaborative environments to deliver measurable outcomes for patients and customers. I specialize in end-to-end data and AI solutions—from data ingestion and governance to production-grade ML models and GenAI workflows. My passion is solving real-world problems through robust architectures, clean code, and purposeful experimentation, all while keeping security and observability at the forefront.…Hi, I'm Piyush Khedkar, a versatile full-stack professional with experience in healthcare and SaaS. I design scalable cloud-native applications, build RESTful APIs, and deploy AI-driven solutions using Python, AWS, and Snowflake. I enjoy turning complex data into actionable insights and thrive in collaborative environments to deliver measurable outcomes for patients and customers. I specialize in end-to-end data and AI solutions—from data ingestion and governance to production-grade ML models and GenAI workflows. My passion is solving real-world problems through robust architectures, clean code, and purposeful experimentation, all while keeping security and observability at the forefront.

Available to hire

Hi, I’m Piyush Khedkar, a versatile full-stack professional with experience in healthcare and SaaS. I design scalable cloud-native applications, build RESTful APIs, and deploy AI-driven solutions using Python, AWS, and Snowflake. I enjoy turning complex data into actionable insights and thrive in collaborative environments to deliver measurable outcomes for patients and customers.

I specialize in end-to-end data and AI solutions—from data ingestion and governance to production-grade ML models and GenAI workflows. My passion is solving real-world problems through robust architectures, clean code, and purposeful experimentation, all while keeping security and observability at the forefront.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

Data Engineer Consultant at Premier HealthCare

May 31, 2025 - October 14, 2025

Consulted core Data Engineering team; implemented medallion architecture on Snowflake leveraging S3 Iceberg as the data lake; automated ETL pipelines using AWS (Glue, S3, Lambda, EC2) with Elasticsearch indexing; tuned queries and slow logs to reduce P95 latency for scalable real-time analytics. Engineered ETL workflows with PySpark and SQL to process high-volume healthcare data into Snowflake and AWS Glue; designed RESTful and GraphQL APIs exposing curated patient insights securely for analytics and GenAI apps. Optimized complex SQL queries in Redshift using CTEs, window functions, and materialized views to speed analytics.

Data Engineer Consultant at Premier HealthCare

May 1, 2025 - October 14, 2025

Consulted with the core Data Engineering team to implement a medallion architecture on Snowflake using S3 Iceberg as the data lake to standardize healthcare data ingestion and reporting pipelines. Automated ETL pipelines using AWS (Glue, S3, Lambda, EC2) integrated with Elasticsearch for indexing curated datasets, tuning queries and slow logs to reduce P95 search latency. Engineered ETL workflows with PySpark and SQL to process high-volume healthcare datasets into Snowflake and AWS Glue, designing RESTful and GraphQL APIs to securely expose patient insights to analytics teams and GenAI applications. Optimized SQL queries in AWS Redshift using CTEs, window functions, and materialized views to speed analytics.

AI Engineer at Premier HealthCare

May 1, 2025 - Present

Prototyped an AI chatbot with long-term memory using LLMs, vector DBs, and RAG; integrated a summarisation agent with LangChain and deployed via AWS API Gateway to securely handle patient inquiries. Delivered client-facing demos resulting in 3 departmental POCs and proposed architectures with potential ARR impact of $500K–$750K. Deployed AI agents and MCP servers in production on AWS (EKS, S3, Snowflake) integrated with Amazon Bedrock through FastAPI, enabling secure, scalable GenAI workflows. Built RESTful API endpoints exposing PyTorch-based NLP engagement propensity models to React + Django for real-time insights, applying observability and domain context for tuned language models.

AI Engineer at Premier HealthCare

May 1, 2025 - Present

Led development of an AI chatbot with long-term memory using LLMs, vector databases, RAG, and prompt engineering; deployed via AWS API Gateway to securely handle patient inquiries. Delivered live demos that spurred 3 departmental POCs and proposed architectures with potential ARR impact of $500K–$750K. Deployed AI agents and MCP servers on AWS (EKS, S3, Snowflake) integrated with Amazon Bedrock through FastAPI for secure, scalable GenAI workflows. Built RESTful endpoints exposing PyTorch NLP engagement propensity models for real-time insights, interfacing with React + Django for frontend/backend integration.

Data Engineer Consultant at Premier HealthCare

May 1, 2025 - October 14, 2025

Advised core Data Engineering team, implemented medallion architecture on Snowflake by leveraging S3 Iceberg as the data lake to standardize healthcare data ingestion and reporting pipelines. Built and automated ETL pipelines using AWS (Glue, S3, Lambda, EC2) integrated with Elasticsearch for indexing curated datasets while tuning queries and slow logs to reduce P95 search latency and support scalable real-time analytics. Engineered ETL workflows using PySpark and SQL to process high-volume healthcare data sets into Snowflake, AWS Glue and designed RESTful and GraphQL APIs that exposed curated patient insights securely to analytics teams and GenAI applications. Optimized complex SQL queries in AWS Redshift using CTEs, window functions, and materialized views to speed up analytics and reduce query runtime by 150ms.

AI Engineer at Premier HealthCare

May 1, 2025 - Present

Prototyped an AI chatbot with long-term memory using LLMs, vector databases, RAG, and prompt engineering; integrated an AI summarisation agent with LangChain deployed via AWS API Gateway to securely handle patient inquiries. Delivered client-facing demos of a patient inquiry resolution AI chatbot, leading to 3 departmental POCs and proposed architectures with potential ARR impact of $500K–$750K. Deployed AI agents and MCP servers in production on AWS (EKS, S3, Snowflake) integrated with Amazon Bedrock through FastAPI, enabling secure and scalable orchestration of patient data queries and GenAI workflows from concept to production.

Data Engineer Consultant at Premier HealthCare

May 1, 2025 - October 14, 2025

Consulted with the core Data Engineering team to standardize healthcare data ingestion and reporting. Implemented a medallion architecture on Snowflake using S3 Iceberg as the data lake; automated ETL pipelines with AWS Glue, S3, Lambda, and EC2; integrated with Elasticsearch for indexing; tuned queries and slow logs to reduce P95 latency for real-time analytics. Engineered ETL workflows using PySpark and SQL to process high-volume datasets into Snowflake; designed RESTful and GraphQL APIs exposing curated patient insights for analytics and GenAI applications. Optimized SQL queries (CTEs, windows, materialized views) to reduce runtime.

AI Engineer at Premier HealthCare

May 1, 2025 - Present

Prototyped an AI chatbot with long-term memory using LLMs, vector DBs, and RAG; integrated an AI summarisation agent with LangChain and deployed via AWS API Gateway to securely handle patient inquiries. Delivered client-facing demos of a patient inquiry resolution AI chatbot, leading to 3 departmental POCs and proposed architectures with potential ARR impact of $500K–$750K. Deployed AI agents and MCP servers in production on AWS (EKS, S3, Snowflake) integrated with Amazon Bedrock through FastAPI, enabling secure and scalable orchestration of patient data queries and GenAI workflows from concept to production. Built RESTful API endpoints exposing PyTorch-based NLP engagement propensity models to React + Django frontends for real-time insights and customized language model tuning.

Data Engineer at HealthCare.com

May 31, 2024 - October 14, 2025

Orchestrated ingestion/transformation of 10M+ Medicare/Medicaid & PII records using PySpark with AWS Glue, Lambda, and S3 into Snowflake for cross-functional consumption. Built and deployed predictive models (LTV, churn) using AWS SageMaker, integrating SQL (Snowflake) and NoSQL (JSON session logs in S3). Automated clickstream ETL pipelines using dbt and GitHub Actions for CI/CD, ensuring data lineage and reliable deployments. Led analytics for health insurance clickstream data to optimize GTM campaigns, achieving a 10% lift in engagements and CTR, generating over $100K in additional revenue.

Data Engineer at HealthCare.com

May 1, 2024 - October 14, 2025

Orchestrated ingestion and transformation of 10M+ Medicare/Medicaid & PII records using PySpark with AWS Glue, Lambda and S3 into Snowflake for cross-functional consumption. Built and deployed predictive models (LTV, churn) using AWS SageMaker, integrating SQL (Snowflake) and NoSQL (JSON session logs in S3) datasets processed through AWS Glue. Automated clickstream ETL pipelines using dbt and GitHub Actions CI/CD to ensure data lineage and reliable deployments. Led analytics for health insurance clickstream data to drive growth strategies and GTM campaigns, achieving a 10% increase in engagements and CTR and over $100K in additional revenue.

Data Engineer at HealthCare.com

May 1, 2024 - October 14, 2025

Orchestrated ingestion and transformation of 10M+ Medicare/Medicaid & PII records using PySpark with AWS Glue, Lambda and S3 into Snowflake for cross-functional consumption using ETL. Built and deployed predictive models (LTV, churn) using AWS SageMaker; integrating both SQL (Snowflake) and NoSQL (JSON session logs in S3) datasets processed through AWS Glue to improve the customer funnel. Automated clickstream ETL pipelines using dbt and GitHub Actions CI/CD to ensure version control, data lineage, and reliable deployments. Led analytics for health-insurance clickstream data to drive growth strategies and optimize GTM campaigns, targeting high-yield channels to achieve a 10% increase in engagements and CTR, resulting in over $100K in additional revenue.

Data Engineer at HealthCare.com

May 1, 2024 - October 14, 2025

Orchestrated ingestion and transformation of 10M+ Medicare/Medicaid & PII records using PySpark with AWS Glue, Lambda, and S3 into Snowflake for cross-functional consumption. Built and deployed predictive models (LTV, churn) using AWS SageMaker, integrating both SQL (Snowflake) and NoSQL (JSON session logs in S3) datasets processed through AWS Glue to improve the customer funnel. Automated clickstream ETL pipelines using dbt and GitHub Actions CI/CD to ensure data lineage and reliable deployments. Led analytics for health insurance clickstream data to optimize GTM campaigns, driving a 10% increase in engagements and CTR, contributing to over $100K in incremental revenue.

Data Engineer at Intelliswift

April 30, 2022 - October 14, 2025

Implemented DataHub metadata ingestion framework using YAML configurations and Python scripts to pull JSON data from PostgreSQL and Snowflake, applying table/column-level data lineage for governance. Built real-time AWS data pipelines with Kinesis, Glue, and S3 for high-throughput analytics, migrating from GCP to AWS. Designed scalable data models using dbt and star schema in Snowflake with clustering keys to optimize performance and reduce latency. Added unit testing, logging, and error handling for data quality; containerized ETL workflows with Docker and used Terraform for automated cloud provisioning.

Data Engineer at Intelliswift

April 1, 2022 - October 14, 2025

Implemented DataHub's metadata ingestion framework using YAML configurations and Python to pull JSON data from PostgreSQL and Snowflake, applying table- and column-level data lineage for governance. Built real-time AWS data pipelines with Kinesis, Glue, and S3 for high-throughput analytics, migrating from GCP to AWS. Crafted scalable data models using dbt and star schema in Snowflake with clustering keys to optimize performance and reduce latency. Integrated unit testing, logging, and error handling in Python for data quality across the system. Containerized ETL workflows with Docker and automated cloud provisioning using Terraform.

Data Engineer at Intelliswift

April 1, 2022 - October 14, 2025

Implemented DataHub's metadata ingestion framework using YAML configurations and Python scripts to pull JSON data from PostgreSQL database, Snowflake and apply table- and column-level Data Lineage for enhanced Data Governance. Built real-time AWS data pipelines with Kinesis, Glue, and S3 for high-throughput analytics migrating from GCP into AWS services. Crafted scalable data models using dbt and star schema in Snowflake with clustering keys to enhance performance optimization and reducing latency in high volume reporting for clients. Integrated unit testing, logging, error handling in Python, ensuring easy debugging and consistent Data Quality across the system. Containerized ETL workflows using Docker and leveraged Terraform to automate cloud infrastructure provisioning for our clients.

Data Engineer at Intelliswift

April 1, 2022 - October 14, 2025

Implemented DataHub's metadata ingestion framework using YAML configurations and Python to pull JSON data from PostgreSQL and Snowflake, applying table- and column-level data lineage for governance. Built real-time AWS data pipelines with Kinesis, Glue, and S3 for high-throughput analytics, migrating workloads from GCP to AWS. Crafted scalable data models using dbt and Snowflake, including star schemas with clustering keys to improve performance and reduce latency. Added unit tests, logging, and error handling to ensure data quality. Containerized ETL workflows with Docker and automated cloud provisioning with Terraform.

Data Scientist at Symbiosis Centre For Applied AI

June 30, 2021 - October 14, 2025

Designed and optimized a DistilBERT model (PyTorch) for lead scoring, boosting F1 by 14% and reducing time-to-contact by 18%. Applied regression, A/B testing, segmentation, and causal inference using Google Analytics to enhance funnel performance and ROI; developed interactive dashboards with Tableau & Sigma to monitor customer ROI initiatives.

Data Scientist at Symbiosis Centre For Applied AI

June 1, 2021 - October 14, 2025

Designed and optimized a DistilBERT model (PyTorch) for lead scoring, boosting F1 score by 14% and reducing time-to-contact by 18%. Applied regression, A/B testing, segmentation, and causal inference using Google Analytics to enhance funnel analytics, LTV, and churn prediction. Developed interactive dashboards with Tableau & Sigma, incorporating moving averages to monitor ROI initiatives.

Data Scientist at Symbiosis Centre For Applied AI

June 1, 2021 - October 14, 2025

Designed and optimized a DistilBERT model (PyTorch) for lead scoring, boosting F1 score by 14% reducing time-to-contact by 18%. Applied regression, A/B testing, segmentation, and causal inference using Google Analytics to enhance Funnel, LTV churn prediction. Developed interactive dashboards with Tableau & Sigma, incorporating moving averages, growth to monitor customer ROI initiatives.

Data Scientist at Symbiosis Centre For Applied AI

June 1, 2021 - October 14, 2025

Designed and optimized a DistilBERT model (PyTorch) for lead scoring, boosting F1 by 14% and reducing time-to-contact by 18%. Applied regression, A/B testing, segmentation, and causal inference to enhance funnel metrics, LTV and churn prediction. Built interactive dashboards with Tableau & Sigma to monitor ROI initiatives and campaign performance.