Mobile Data Visualization Engineer - Interactive Technical Charts

 Posted 2 hours ago
  
 India
  
5-10 years experience
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AI Summary

Own the visualization layer for power-quality analysis software, creating high-performance interactive charts for smartphones and tablets. Implement complex data rendering techniques and maintain the chart engine through production profiling and debugging.

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.

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.

What you will do as a Data Visualization Engineer...

  • 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

What we are looking for…

  • 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

Desirable (but not required):

  • 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

Benefits and perks…

  • 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

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