Data Engineer of 5 years of experience with hands-on ownership of financial data infrastructure in high-stakes, regulated environments. At Centene Corporation, I own end-to-end pipelines processing Medicare and Medicaid financial data across a network of 60-70 hospitals — environments where a wrong number isn't a bug, it's a regulatory and financial liability.
I led the migration of enterprise healthcare data off Palantir onto Snowflake, cutting Medicaid/Medicare report generation time by 60% and reducing redundant datasets by 25% across the org. I built the Kafka-based CDC streaming architecture that brought our reporting layer to near-real-time, standardised transformation logic across dbt models, and built the data quality and observability frameworks that catch bad data before it reaches financial stakeholders.
Domain-wise, my depth is in healthcare financial reporting and regulatory compliance, with earlier work in quantum computing (Python/Qiskit, IBM) and predictive modelling for nonprofit programs (PySpark/SageMaker behavioural-risk models, Delta Analytics fellowship).
Currently exploring analytics and data engineering roles where the core problem is turning messy, high-stakes data into something people can actually trust."
Remote: Preferred
Willing to relocate: Yes
Technologies: SQL, Python, PySpark, AWS, Palantir, Snowflake, dbt, Databricks
Résumé/CV: https://blue-cloud-565.linkyhost.com
Email: thotasadhvika@gmail.com
Data Engineer of 5 years of experience with hands-on ownership of financial data infrastructure in high-stakes, regulated environments. At Centene Corporation, I own end-to-end pipelines processing Medicare and Medicaid financial data across a network of 60-70 hospitals — environments where a wrong number isn't a bug, it's a regulatory and financial liability.
I led the migration of enterprise healthcare data off Palantir onto Snowflake, cutting Medicaid/Medicare report generation time by 60% and reducing redundant datasets by 25% across the org. I built the Kafka-based CDC streaming architecture that brought our reporting layer to near-real-time, standardised transformation logic across dbt models, and built the data quality and observability frameworks that catch bad data before it reaches financial stakeholders.
Domain-wise, my depth is in healthcare financial reporting and regulatory compliance, with earlier work in quantum computing (Python/Qiskit, IBM) and predictive modelling for nonprofit programs (PySpark/SageMaker behavioural-risk models, Delta Analytics fellowship).
Currently exploring analytics and data engineering roles where the core problem is turning messy, high-stakes data into something people can actually trust."