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Esa Khatiwada

@esakhatiwada

Senior Data Engineer at Cardinal Health who re-engineered lakehouse ingestion and cut batch processing runtimes by 40%+.

United States

Message

At Cardinal Health, I architect and own production-grade data platforms across GCP and AWS for pharmaceutical distribution, supply chain, finance, and healthcare analytics. I re-engineered legacy ingestion workflows into a Bronze, Silver, and Gold lakehouse architecture, and optimized PySpark pipelines to reduce batch runtimes by 40%+.

For The Hartford, I developed insurance data pipelines and built an event-driven claims ingestion pipeline that reduced fraud data latency by 48%. I also re-engineered legacy SSIS workflows as AWS Glue jobs, reducing nightly batch runtime by 43%.

Earlier, I developed retail ETL workflows at Target and supported Azure data pipelines for Zurich North America. I’ve also worked in DevOps at Fullstack, and I mentor data engineers through architecture reviews, optimization, and code reviews.

Experience

Work history, roles, and key accomplishments

Current

Senior Data Engineer

Current

Cardinal Health

Nov 2024 - Present (1 year 11 months)

Architected and owned production-grade multi-cloud data platforms across GCP and AWS, leveraging Databricks, Delta Lake, BigQuery, Amazon S3, and Snowflake. Designed scalable ETL/ELT pipelines and led performance and cost optimization initiatives.

Data Engineer

The Hartford

May 2021 - Oct 2024 (3 years 5 months)

Developed and supported production data pipelines for commercial and personal insurance lines, integrating policy, claims, underwriting, premium, coverage, and loss data. Built event-driven ingestion pipelines and optimized Snowflake workloads, reducing compute spend by 31%.

AWS Glue S3 AWS Kinesis Lambda AWS MWAA Athena Redshift Spectrum Cloudwatch Lake Formation QuickSight Databricks Delta Lake Snowflake DBT PySpark Spark SQL Python SQL Airflow Terraform AWS CodePipeline Git CI CD

Data Engineer

Zurich North America

Jan 2020 - Apr 2021 (1 year 3 months)

Assisted in maintaining Azure Data Factory pipelines and developed PySpark and SQL transformations in Azure Databricks. Supported data movement through Bronze, Silver, and Gold layers and added validation checks to improve data accuracy.

Azure Data Factory ADLS Gen2 Azure Databricks Delta Lake Azure Synapse Azure SQL PySpark Python SQL Power BI azure monitor Git Azure DevOps

ETL Developer

Target

Mar 2019 - Jan 2020 (10 months)

Developed and maintained large-scale ETL workflows using Informatica PowerCenter and SSIS, supporting high-volume sales, inventory, and promotional data. Led performance tuning initiatives and implemented SCD Type 2 logic for accurate historical tracking.

Informatica PowerCenter SSIS SQL Server Oracle Teradata DB2 Pl SQL BASH Shell Scripting Crystal Reports SSRS TFS SCD ETL Data Warehouse Star Schemas Performance Optimization

Devops Engineer

Fullstack

Apr 2018 - Feb 2019 (10 months)

Maintained Jenkins jobs for Django and Flask applications, supported deployments, and wrote Bash and Python scripts for automation. Assisted with AWS infrastructure and Terraform configurations, and contributed to reducing incident resolution time by 30%.