Sheldon Lee Kemper

Databricks Data Engineer @Capgemini

London, GB

Responsible for designing and building high-performance data pipelines that utilize Databricks and Apache Spark to extract, transform, and load data into Azure Data Lake Storage and related Azure services. This role develops and maintains secure data warehouses and lakehouses by implementing robust data models, comprehensive data quality checks, and stringent governance practices to ensure reliable and accurate information. It also encompasses the building and deployment of AI/ML models by integrating Machine Learning into data pipelines, leveraging Databricks ML and Azure ML to develop predictive models that drive actionable business insights.Additionally, this position monitors and optimizes data pipelines and infrastructure through the analysis of performance metrics, identification of bottlenecks, and implementation of strategic optimizations to enhance efficiency and scalability. Collaboration with cross-functional teams—including business analysts, data scientists, and DevOps engineers—is key to ensuring successful data platform implementations. Continuous learning and adaptation to the evolving landscape of big data technologies and best practices are fundamental to delivering innovative and future-proof solutions.

Harvard University

Agentic AI, AI Strategy, Governance, and Workflow Design