• Solid computer science fundamentals such as algorithms, data structures, multithreading, object-oriented development, distributed applications, client-server architecture.
• Design and implement Machine learning models and data ingestion pipelines.
• Develop and support a platform that enables data scientists to rapidly develop, train, and experiment with machine learning models.
• Expand and optimize data pipelines, data flow, and collection for cross-functional teams.
• Create and maintain optimal data pipeline architecture by assembling large, complex data sets to meet functional and non-functional business requirements.
• Identify and implement internal process improvements, including automating manual processes, optimizing data delivery, and redesigning infrastructure for greater scalability.
• Work with architecture, data, and design teams to assist with data-related technical issues and support data infrastructure needs.