Umar Khan Email & Phone Number

San Francisco, Ca, Us

Leadership Highlights• Lead a team of 4 engineers and data scientists, providing technical guidance and mentorship• Responsible for building and managing high-performing data pipelinesKey Technical Achievements• Designed and implemented a highly scalable and fault-tolerant data infrastructure on Databricks, leveraging: - Apache Spark for high-performance processing and data transformation - Kafka for real-time data ingestion and event streaming - Airflow for workflow orchestration and automation• Built a large-scale data pipeline capable of handling tens of thousands of data points per minute, from electric vehicle chargersImpact• Enabled real-time data-driven decision making across the organization• Supported business intelligence, billing, analytics, customer frontends, and reporting with scalable data infrastructure• Improved data processing efficiency and reliability, ensuring accurate insights for business stakeholders

San Francisco, Ca, Us

Ca, Us

Leadership Highlights• Led a team of 20 software and QA engineers in developing a cutting-edge platform for genetic data analysis• Provided technical guidance and oversight to ensure project deliverables met high standardsKey Technical Achievements• Migrated from monolithic to distributed micro-service-based architecture, improving engineering team efficiency and system performance• Designed a petabyte-scale data lake for storing and analyzing genetic data, enabling near real-time reads over trillions of records• Built a business intelligence tool using Apache Spark for marketing and executive decision making• Leveraged Databricks, Apache Spark, and AWS cloud-based technologies to optimize performance and efficiencyImpact• Improved system performance and scalability• Enhanced data analysis capabilities for genetic research• Provided critical insights for informed decision making in marketing and executive leadership

Leadership Highlights• Led a team of 5-10 engineers in developing a platform for financial statement analysis using machine learning• Provided technical guidance and mentorship to team membersKey Technical Achievements• Designed and implemented an MLOps framework for large-scale training of machine learning models• Developed a micro-service based architecture built on Kubernetes, ensuring scalability and reliabilityImpact• Improved the efficiency and accuracy of financial statement analysis using machine learning• Enabled the scaling of machine learning model training and deployment• Enhanced the overall reliability and maintainability of the platform