Mobile Data Visualization Engineer - Interactive Technical Charts
Synmatch AI
IndiaremotePosted 1 month ago
Skill Required
Data-Visualization-EngineerMobile-DevelopmentScientific-VisualizationCharting-DevelopmentData-Visualization-EngineeringData-Visualization-DeveloperData-Visualization-SpecialistMobile-UI-EngineerFrontend-EngineerData EngineerTechnical LeadEngineeringPower BIbuildingTableaudesignFigmaandAIFulltime
Key highlights
- Visualization layer is the core product; you own the look and feel of every chart.
- Deliver the first version of a new chart within a week and iterate with real users.
- On‑call rotation for rendering and performance regressions is required.
- Charts must handle gigabyte‑scale, multi‑channel, multi‑phase recordings.
- Large‑dataset performance expertise (LOD downsampling, viewport culling, profiling on lower‑end devices) is mandatory.
- Charts are the core experience of a visualization‑first product.
Role overview
For a PQ analyst, the chart is the product. They live inside it for hours zooming from a week-long campaign down to a single half-cycle, overlaying multiple recordings, brushing across phases, reading harmonic spectra to the 50th order. Join Synmatch AI's client on the founding engineering team building the next generation of power-quality analysis software and own the visualization layer that makes all of that feel instant and effortless. Our client has decades of expertise in electrical safety, e-mobility, medical technology, power quality, and energy management systems. You'll create visualization experiences for smartphones and tablets that support field workflows and offline-first operations for professionals working with high-quality measurement technology.
Responsibilities
- Make Large Datasets Feel Light: Implement level-of-detail downsampling, viewport culling, sub-pixel zoom/pan, and time-aligned overlays at interactive frame rates on tablets
- Render the PQ Vocabulary: Build oscillographic waveforms with cycle markers, RMS-vs-time strip charts, harmonic spectrum bars to the 50th order, phasor diagrams, harmonic heatmaps, CBEMA/ITIC tolerance curves, scatter/PDF plots, and event timelines
- Design Analysis-Grade Interactions: Smooth pinch/scroll on touch, trackpad, and mouse-wheel; crosshair with multi-series readout; brush-to-zoom; synchronized cursors across stacked charts; drill-down on event markers
- Get Visual Details Right: Color palettes that work on screen and print, accessible contrast, type and tick spacing respecting expert reading habits
- Profile Relentlessly: Performance benchmarking and profiling to improve user experience and optimize metrics footprint
- Ship Usable v1, Then Iterate: First cut of a new chart in a week, refined with team and real users in the open
- Operate the Chart Engine: Share on-call rotation for rendering and performance regressions, turning each into a permanent benchmark
- You'll work closely with a power-quality analyst on what a 'correct' chart actually means in this domain
- The Lead Architect sets the boundaries; the look and feel of every chart, you own
- You build it, you run it: the chart engine you ship is the one you also profile in production, debug from field reports, and evolve as datasets grow
Requirements
- Custom Chart Engineering: Built non-trivial visualization beyond what off-the-shelf libraries can do not just configuration
- Interaction-Design Instinct: Zoom, pan, brush, crosshair, drill-down—you know what good feels like and you've built it
- Large-Dataset Performance Discipline: LOD downsampling, viewport culling, profiling tools, frame-time budgets on real lower-end devices
- Visual Taste Plus Engineering Rigor: Equally comfortable in Figma and in a profiler
- Operational Ownership: You expect to be on call for the rendering layer you build, including platform-specific regressions
- Listener Mindset: You ask expert users how they actually read a chart before deciding how to draw it
Nice to have
- Prior data-viz heavy work: trading-desk frontends, BI tools (Tableau, Power BI), genomics/biomedical viz, or scientific software
- Background in signal-heavy domains where waveforms or spectra are the primary medium
- Golden-test or visual-regression experience for charts
- Test-driven development as default practice for non-rendering portions of the chart engine
Additional details
- Visualization-First Product: Charts are the core experience here, not a side panel
- Specialist Team: Work alongside a dedicated power-quality analyst, lead architect, data-processing engineer, and hardware product teams
- Real-World Dataset Complexity: Multi-channel, multi-phase, multi-aggregation-interval, gigabyte-scale recordings
- Made-in-Germany Quality: Decades of measurement-instrument heritage with a customer base that notices when the numbers are right
- Originally posted on Himalayas