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Muhammad Hamza Zaidi

@muhammadhamzazaidi

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Lead Data Engineer at HealthVerity who unified 15+ healthcare data sources in a governed Lakehouse.

United States

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At HealthVerity, I lead data engineering initiatives for a healthcare intelligence platform serving more than 9 million entities. I designed and owned a Databricks and AWS Lakehouse that brought together over 15 healthcare data sources in a governed platform.

I built and optimized more than 50 batch and real-time pipelines for claims normalization, eligibility matching, and clinical data standardization. I also designed event-driven ingestion and implemented governance and data quality frameworks supporting HIPAA/HITRUST compliance.

At Lovelytics, I led financial and healthcare data engineering projects, including modernizing legacy SSIS pipelines with Azure Data Factory, Databricks, and Synapse Analytics. I also developed streaming and change-data-capture pipelines for financial systems and healthcare claims.

At Amplitude, I developed ETL and reverse ETL pipelines for SaaS analytics, along with dimensional models and reporting layers. I hold Google Cloud, Microsoft Azure, AWS, Databricks, and Snowflake data engineering certifications.

Experience

Work history, roles, and key accomplishments

Current

Lead Data Engineer

Current

HealthVerity

May 2023 - Present (3 years 5 months)

Led data engineering initiatives for a healthcare intelligence platform, designing and owning end-to-end Lakehouse architecture on Databricks and AWS. Built and optimized over 50 batch and real-time ETL/ELT pipelines, implemented data governance frameworks for HIPAA/HITRUST compliance, and established monitoring and SLA tracking frameworks.

Senior Data Engineer

Lovelytics

Jun 2019 - Apr 2023 (3 years 10 months)

Led financial and healthcare data engineering projects, migrating legacy SSIS pipelines to Azure cloud platforms and implementing ACID-compliant ETL workflows. Built low-latency streaming pipelines and CDC-based ingestion, developed semantic data models in Looker and Power BI, and optimized ETL pipelines for performance.

Data Engineer

Amplitude

Mar 2016 - Jun 2019 (3 years 3 months)

Designed and developed scalable ETL pipelines using Python, SQL, Apache Airflow, and dbt to ingest SaaS event data into Snowflake and Amazon Redshift. Developed reverse ETL pipelines, designed dimensional data models and semantic reporting layers, and implemented Infrastructure-as-Code with Terraform and containerized deployments.