Autonomous Systems Data Mining Engineer, Skydio

• 3+ years of experience in data engineering, backend engineering, or infrastructure roles
• Exposure to robotics, autonomy, or real-world sensor data pipelines
• Strong proficiency in Python (or similar language) and SQL
• Experience designing scalable data pipelines with tools such as Apache Spark, Airflow, dbt, or equivalent
• Familiarity with log processing, time-series analysis, or working with large volumes of semi-structured data
• Ability to work cross-functionally with ML engineers, autonomy engineers, and product stakeholders
• Systems thinking: you enjoy untangling complexity and designing elegant abstractions that empower others
• Bonus: experience working with robotics, sensor data, or computer vision pipelines

Desirable

• We are seeking a Data Engineer with a systems mindset to own and simplify access to the massive amount of data generated by our fleet of autonomous drones
• You will play a key role in improving how engineers, researchers, and product stakeholders interact with logs, video, sensor data, and derived analytics, making it easier to extract insights and build better autonomy features
• This role will partner closely with autonomy engineers, ML researchers, QA, and platform teams to design data pipelines, build indexing/search capabilities, and develop tools that unlock the value of our data
• Data Discovery & Accessibility: Design systems to unify scattered data sources (logs, telemetry, analytics tables, media, etc.) into easily discoverable and queryable formats
• Smart Dataset Generation: Enable efficient curation of machine learning datasets by tagging, indexing, and filtering for relevant scenarios (e.g., environmental conditions, sensor behavior, scene attributes)
• Telemetry & Log Intelligence: Build tools to automatically surface anomalies, regressions, or key signatures in logs and telemetry data (e.g., CPU usage spikes, sensor noise, degraded conditions)
• Software Performance Monitoring & Tooling: Develop mechanisms to rapidly compare releases and surface regressions in performance metrics, resource usage, and data quality
• Architect and maintain scalable data pipelines and services to index, enrich, and query multimodal autonomy data (e.g., time series, media, tabular analytics)
• Collaborate with autonomy and ML teams to understand data usage patterns and build tools that streamline their workflows
• Develop efficient methods for search, tagging, and filtering over structured and unstructured data
• Help design systems to label and retrieve rare or complex scenarios, both automatically at ingestion and via manual search
• Build dashboards and visualizations to support release monitoring and anomaly detection across a variety of system health signals