Neil Saunders

I am a Senior Data Engineer with extensive experience in designing and deploying scalable data pipelines, particularly within the financial and healthcare sectors. At Goldman Sachs, I significantly improved data processing efficiency by modernizing legacy ETL workflows and implementing robust data quality frameworks. My work has enabled near real-time analytics for investment risk metrics, enhancing compliance readiness and operational efficiency.

Previously, at Johnson & Johnson, I led the development of a centralized data warehouse for global supply chain operations, which facilitated unified analytics across various systems. My expertise in Azure technologies, including Data Factory and Synapse, has allowed me to automate data ingestion processes, ensuring data consistency and traceability for compliance reporting. I thrive in collaborative environments, working closely with quant teams and data scientists to deliver high-value datasets that drive strategic decision-making.