Data Engineer, Nimble Robotics

• Fast learner with a strong work ethic, high performance standards, and ambition
• 1-4 years of experience in a tech company or fast-growing startup
• BS/MS/PhD in Computer Science, Mathematics, Computer Engineering, or a related field, or equivalent practical experience
• Proficiency in writing production-grade code in at least one of: Python, Java, Rust, Go, or Scala
• Strong debugging skills and the ability to diagnose and resolve issues efficiently
• Experience with Kafka and/or Spark
• Experience working with AWS or other cloud platforms
• Willing to work extended hours and weekends if needed

Desirable

• Help us advance our robotics moonshot by scaling our data engineering efforts
• Drive design and development of data infrastructure across our products and internal tools
• You will play a critical role in working with our world-class cross-functional team to architect and build the world’s most advanced robotic systems for the world’s biggest robotics opportunity!
• Design and maintain scalable, reliable data pipelines
• Ensure timely and efficient data collection, processing, and availability
• Integrate data from multiple sources for both batch and streaming analytics
• Manage and optimize the data lakehouse for performance and reliability
• Apply best practices in data modeling, pipeline design, and query optimization
• Monitor pipeline performance and troubleshoot issues
• Develop and manage ETL/ELT processes for loading data into data warehouses and data lakes
• Maintain data integrity and consistency across systems
• Collaborate with engineering, product, finance, bizops, and other teams to understand data needs and deliver solutions
• Provide data engineering support to ensure data accessibility and usability company-wide
• Define and enforce data quality standards
• Implement data governance to ensure compliance with internal and external policies
• Stay current with industry trends and technologies in data engineering
• Continuously improve data processes and infrastructure for efficiency and scalability
• Document data engineering processes, designs, and architectures