Hamza Khawar

I’m an Azure-specialised Data Engineer with 7+ years of experience building regulatory-grade, cloud-native data platforms in the biopharmaceutical and real estate sectors. I bring a deep command of the Microsoft data ecosystem—Azure Data Factory, Azure Databricks, Synapse Analytics, and ADLS Gen2—combined with hands-on expertise in dbt, Python, and Snowflake.

At UBC, I architected end-to-end ELT pipelines on Azure Data Factory to ingest clinical study data, RWE feeds, and patient access data from 15+ pharmaceutical partners into ADLS Gen2, processing 50M+ healthcare records annually. I designed and implemented a Medallion Architecture (Bronze/Silver/Gold) with Azure Databricks, and built dbt transformation models on Azure Synapse Analytics to support drug safety signal detection, adverse event reporting, and REMS program compliance metrics.

I’m known for turning complex compliance requirements (HIPAA, PHI, pharmacovigilance) into scalable, auditable pipeline architecture teams can rely on. I engineered HIPAA-compliant pipelines with PHI de-identification and masking logic in Python, deployed Azure Purview for end-to-end lineage and cataloguing, and built audit-ready pipeline architecture with immutable Bronze-layer logs—while improving operational performance using monitoring and alerting (reducing MTTD by 65%) and streamlining releases via CI/CD (reducing deployment errors by 70%).

Earlier at SERHANT, I delivered multi-market MLS analytics and agent performance warehousing by building Azure Data Factory pipelines, orchestrating workflows with Apache Airflow, and developing dbt models on Snowflake within a star schema data warehouse. I hold the Microsoft Azure Data Engineer Associate (DP-203) and dbt Analytics Engineering certifications, and I mentor teams on Azure best practices, dbt modeling patterns, and HIPAA data handling standards.