Design Deep Dive
Problem 1: Data fragmentation
How I designed a solution for data fragmentation across thousands of vehicle types
Modern vehicles generate thousands of signals, but each manufacturer structures and names them differently.
OEM A
engineRPM
OEM B
EngineSpeed
OEM C
Proprietaryfmt021x
No Universal Schema
Customers can not rely on consistent data structure across their fleet
Broken Analysis
Cloud applications can not consume or compare data consistently
Fragmentation is more than a naming issue. It breaks cross-fleet analysis, increases onboarding time, and forces teams to manually decode signals before any meaningful work can begin.
Research
How I investigated the problem space
Key insights
Automotive Engineers
Workshops to unpack how raw signal files were defined, maintained, and handed off internally
Internal SMEs
Whiteboard sessions with experts who had previously worked inside major OEMs
These sessions helped me map the entire signal lifecycle, from creation inside embedded systems to consumption inside cloud pipelines.
Amazon Fleet Teams
Conversations with teams who consume telemetry at scale and deal with inconsistent signal definitions
Engineers and cloud developers speak different data languages
Engineers think in mechanical terms; cloud developers need structured, typed, hierarchical schemas. No translation layer existed between these worlds.
Team structure creates massive variation in file quality
Large OEMs have full signal-definition teams, while smaller manufacturers rely on one developer juggling everything end-to-end.
Different stakeholders care about different categories of signals
Diagnostics, safety, behavior, drivetrain, battery health—the priorities change depending on who is consuming the data.
Vehicle data was inconsistent, and for legitimate, structural reasons.
Key learnings
Strategic insights from building a flagship service
“Design is not a finishing layer. It is a strategic tool that shapes product direction long before pixels or APIs exist.”
Embedding design early helped align teams, reduce rework, and clarify the product's north star from day one.
“In an engineering-driven culture, trust is earned by showing that design accelerates delivery, not slows it down.”
Translating UX decisions into technical and business outcomes built credibility and momentum across teams.
“Navigating ambiguity meant staying adaptable through change while protecting continuity in vision and experience.”
From shifting priorities to team turnover, design provided stability without sacrificing speed.
“Design became the connective tissue, aligning teams not only within the service, but across the broader AWS IoT organization.”
Shared frameworks, journeys, and artifacts turned diverse perspectives into aligned execution.
Detail design
What I could not assume
One mental model
One use case
One team size
One structure
Respect workflows
Design solution
Cloud-ready
All team sizes
Low friction
Industry standards
Extending my role beyond a UX designer
Fleetwise team at CES 2023 and 2024
Watch data collected by fleetwise being used in real time simulation