Responsibilities

• Design, implement, and manage end-to-end data pipelines that collect, process, and store sensor data from robotic systems.
• Ensure data quality, consistency, and availability for both real-time and historical analysis.
• Implement data transformation, feature engineering, and enrichment techniques to prepare data for training and validation.
• Implement monitoring solutions to track the health and performance of deployed robotic systems and associated data pipelines.
• Analyze performance metrics and proactively identify opportunities for optimization and improvement.
• Collaborate with cross-functional teams to iteratively enhance system efficiency and response times
• Collaborate closely with software developers, machine learning engineers, and robotics teams to ensure alignment on technical requirements and objectives.
• Maintain comprehensive documentation for deployed data pipelines and system architecture.

Qualifications

• Bachelor’s, Master’s, or PhD degree in Computer Science, Software Engineering, or related field.
• 3+ years of experience in data engineering.
• Strong proficiency in programming languages such as Python, Scala, SQL, along with experience with popular data storage systems (e.g. Data Lakes).
• In-depth knowledge of data engineering principles, ETL processes, and data storage solutions.
• Experience managing and monitoring large sets of unstructured and high frequency data
• Familiarity with containerization (e.g., Docker) and orchestration tools (e.g., Kubernetes).
• Experience performing responsibilities related to ML Ops
• Experience with cloud platforms (e.g., AWS, GCP, Azure) and related services.
• Strong problem-solving skills and ability to work in a collaborative, fast-paced environment.