Staff Engineer, Data Analysis (R5290)
Job Description:
We’re looking for a Staff Engineer to lead V-BAT’s fleet data analysis efforts. The V-BAT system produces rich data from real-world flight tests, fielded aircraft, production activity, and simulation runs.
You will own the analysis pipelines, tooling, standards, and metrics that help the team understand fleet-wide system performance derived from information from software and hardware systems. You will facilitate deep studies into flight-critical sensor performance, navigation, communications, and other key aircraft behaviors. You will work closely with DevOps, Flight Software, Flight Test, Production, Quality, and Operations teams to turn complex aircraft data into actionable engineering insight.
What you'll do:
- Lead the technical strategy for V-BAT fleet data analysis across fielded aircraft, flight test, simulation, production, and quality workflows
- Own and improve the pipelines that transform raw flight, simulation, and fleet data into reliable engineering metrics, reports, and analysis products
- Conduct fleet-wide studies to identify trends in hardware quality, system performance, reliability, and operational behavior
- Analyze flight-critical sensor performance, GNSS-denied navigation performance, communications behavior, and other aircraft subsystems that are critical to mission success
- Standardize the team’s analysis methods across online tools, Jupyter notebooks, automated Python scripts, and legacy Matlab workflows
- Define best practices for analysis methods, data review, documentation, validation, reproducibility, and contribution workflows
- Build automated Python workflows that make high-value metrics easily accessible to engineering, production, quality, and leadership teams
- Partner with DevOps to build, deploy, maintain, and scale the infrastructure required for automated analysis pipelines and dashboards
- Work with Software, GNC, Embedded, Flight Test, Systems, Production, Quality, and Operations teams to define metrics that reflect aircraft performance and product health
- Support anomaly investigations, root-cause analysis, release readiness, production quality improvements, and customer-impacting fleet investigations with rigorous data analysis
- Mentor engineers on effective data analysis practices and raise the quality bar for data-driven engineering decisions across the V-BAT team
Required qualifications:
- 5+ years of relevant experience with a Bachelor’s degree in Computer Science, Data Science, or a related technical field
- Strong Python skills and experience building data analysis tools, automated analysis workflows, or data pipelines
- Experience analyzing data from fielded physical products such as aerospace systems, automotive systems, robotics platforms, commercial electronics, IoT devices, industrial equipment, or similarly complex real-world systems
- Experience working with large, messy datasets from deployed products, test events, simulations, production systems, or operational environments
- Ability to translate ambiguous engineering questions into structured analysis, sound conclusions, and clear recommendations
- Strong communication skills and the ability to influence cross-functional engineering, production, quality, and operations teams
Preferred qualifications:
- Experience with flight test data, aircraft telemetry, UAVs, robotics, autonomy, embedded systems, GNC, navigation systems, communications systems, or aerospace sensor suites
- Experience with Matlab, Jupyter, or similar analysis and visualization tools
- Experience building production-quality dashboards, automated reports, data products, or fleet-health monitoring systems
- Experience with databases, cloud storage, data lake architectures, time-series databases, telemetry systems, or data cataloging
- Experience with anomaly detection, trend analysis, statistical process control, reliability analysis, regression detection, or automated validation of complex systems
Skills
As published by lever · 19 questions · 9 written answers
Basics
Which location are you applying for?, Resume/CV, Full name, Email, Phone, Current location, Current company, LinkedIn URL, Twitter URL, GitHub URL, Portfolio URL, Other website
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Written answers (9)
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