About

Christopher Hyatt is an experienced Data Engineer with over 12 years of experience in designing, developing, and implementing data-intensive applications. He is skilled in creating intuitive architecture that enables organizations to effectively analyze and process large volumes of structured and unstructured data. Christopher leverages his sound business acumen and technical expertise to elicit business requirements and guide the delivery of scalable solutions that drive business intelligence and create actionable insights through big data analytics and machine learning. Currently, Christopher is working as a Data Engineering Technical Lead at General Motors, where he is responsible for providing technical leadership in enterprise data governance, data quality and analytics, data mining, data compression, business intelligence, configuration automation, data warehousing, and big data analysis. He is also proficient in strategic technical planning, data architecture, IT system development, data warehouse, stakeholder relationships, project management, big data technologies, and ETL pipeline. Christopher has worked with various organizations in the past, including Engagement Labs and Intel. At Engagement Labs, he served as Director of Analytics, Software Engineer, and Data Engineer, where he developed software and data management solutions to support customer projects. He designed a business intelligence tool to identify correlations between online/offline data and enabled customer data input to create forecasting models based on sales metrics and social interaction data. He also developed an anomaly detection algorithm and an automated infrastructure to analyze data, significantly decreasing the time required to process 4,000 weekly time series data and produce insights for sales and product teams. At Intel, Christopher served as a System Validation Engineer, where he led software development and system validation for power management and multimedia IP blocks designed to support the SoFIA project for smartphone and tablet chip design. He collaborated with design and firmware teams to fix system bugs and automated test development, which resulted in product delivery two months ahead of schedule. Christopher holds a Master of Science degree in Computer Science from Texas State University-San Marcos and a Bachelor of Business Administration degree in Finance and Real Estate from Baylor University-Hankamer School of Business. He is proficient in various technologies, including Data Engineering, Big Data, Senior Software Engineer, ML, Software Engineer, ETL, NLP, Apache Airflow, Scikit, Data Warehouse, Docker, Pandas, Python, C, Research Scientist, infra, and test.