At Viso.ai, I built an Azure data engineering solution for computer-vision detection events from enterprise camera and edge deployments, powering operational analytics for device health, detection accuracy, alerting, and usage.
I developed reusable Azure Data Factory ingestion pipelines and PySpark Databricks workflows that raised data quality from approximately 78% to over 90%. I also created a Silver-layer quality framework that reduced reporting errors by approximately 35% and Gold-layer models supporting Power BI dashboards for 30+ stakeholders.
Previously, I designed multi-source housing-demand analytics pipelines for ESCP Housing Society and translated findings into growth and partnership strategy that contributed to doubling the website's active user base. At HSBC, I supported data migration, batch scheduling, monitoring, and production incident resolution for Risk IT.
I bring hands-on experience with Azure Data Factory, ADLS Gen2, Databricks, PySpark, Synapse Analytics, SQL, and Python, alongside analytics and stakeholder-facing reporting.
