How do you open a 2 GB waveform file on a tablet and let the user pan, zoom, and query it in milliseconds? That's the question this role exists to answer. Join Synmatch AI's client on the founding engineering team building the next generation of measurement analysis software for a global premium provider of measurement instruments. You'll design the storage layout, ingestion pipeline, and query patterns that everything else in the app depends on and keep that data plane healthy in production for years after you ship it.
In a power-quality analysis tool, a beautiful chart with the wrong number is worse than no chart at all. You'll own the mathematical core the algorithms that turn raw voltage and current samples into harmonics spectra, RMS values, flicker indices, sag/swell events, and standards-compliant aggregates. Recordings can span hours at tens of thousands of samples per second across multiple channels and phases. None of that is forgiving of "we'll optimize later."
You'll partner closely with an in-house power-quality analyst and measurement device engineers to translate measurement campaigns into precise on-device data contracts, and with the Lead Architect to ensure storage choices fit the broader system. You build it, you run it: when a customer's 4 GB recording opens slowly six months from now, you profile it, fix it, and write the regression test.
What you will do as an Application Engineer – Measurement Data Processing...
Design On-Device Storage & Ingest Layer: Define and evolve storage (columnar layouts, compression schemes, downsampling pyramids, time-bucket indexes) and ingest layer (streaming, iterator-based parsing of large volumes in Dart with zero full-file slurps FFI to native code where it pays off)
Implement Calculation Kernels: Build processing for event detection (sags, swells, transients), analytical calculations, and standards-compliant aggregations (e.g., IEC 61000-4-x) choosing the right numerics for stability under long aggregation intervals
Plan Schema Evolution & Cloud Sync: Forward- and backward-compatible migrations so customer files from year one still open in year five partial sync, vector clocks, conflict surfaces in close collaboration with Lead Architect
Operate What You Ship: Share on-call rotation for data-plane incidents, lead postmortems on ingest or query regressions, and turn each into permanent test or performance benchmark
Validate Against Reference Vectors: Establish golden test vectors with PQ analyst, prototype in Python/NumPy, and prove production Dart/Rust kernels agree to required precision
What we are looking for…
Time-Series Data Structures: Strong CS fundamentals columnar layouts, compression, downsampling, time-bucket indexing. Hands-on with at least one embedded analytical engine (DuckDB, SQLite/drift, ClickHouse-local, or equivalent)
Streaming Ingest with Memory Discipline: Experience parsing large binary or text files in chunks without loading into memory. Comfortable with mmap, paged readers, and isolate-based pipelines
Applied Math Implementation: Strong in at least one of Dart, C, C++, or Rust; comfortable wiring kernels across FFI boundaries for complex numbers, Fourier analysis, Hilbert transforms, etc.
Data Integrity as a Value: You consider silently losing a sample a critical bug, full stop
Domain Humility: Willing to learn the physics before optimizing the bytes; comfortable working closely with a PQ analyst
Benchmark-First Instincts: You measure before you tune, and write the harness yourself
Desirable (but not required):
Experience with large data volumes using Apache Arrow, Parquet, or FlatBuffers especially with Dart FFI bindings
Prior exposure to measurement, instrumentation, scientific software, or power-quality standards
Python/NumPy/SciPy fluency for prototyping and reference computation
MSc in Electrical Engineering, applied mathematics, or related field
Benefits and perks…
Founding Influence: Contribute to the technical direction of a product defining a category for the next decade
Specialist Team: Work alongside a dedicated power-quality analyst, visualization engineer, and hardware product teams
Real Engineering Culture: ADRs, performance budgets, and reference test vectors are first-class artifacts
Made-in-Germany Quality: Decades of measurement-instrument heritage with a customer base that notices when the numbers are right
