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Publié il y a 9 mois

Geospatial Data Engineer

@ Shearwater Aerospace

Montréal, Québec

TélétravailTemps plein4+ ans d’expérience
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SIGNAUX

En bref

Shearwater Aerospace is hiring a Geospatial Data Engineer, its first geospatial hire, to build the data processing systems behind onboard autonomous flight decisions. The role designs geospatial pipelines, GIS algorithms and real-time APIs for weather-aware route optimization, working with the CTO. Full-time, hybrid in Montreal, with equity ownership offered.

Responsabilités :

  • Design geospatial processing pipelines balancing performance, accuracy and extensibility
  • Build GIS analysis algorithms for weather-aware route optimization
  • Integrate elevation, obstacle, airspace and meteorological datasets
  • Create APIs enabling real-time flight decision-making
  • Establish patterns and tooling as the platform matures

Résumé des exigences :

  • 4+ years building geospatial software (3 with strong shipped systems)
  • Strong knowledge of QGIS and GDAL/OGR
  • Experience with geospatial algorithms and coordinate systems
  • Strong Python with NumPy, Pandas, SciPy, GeoPandas, Rasterio, Xarray, Dask
  • Experience with spatial databases such as PostGIS or Apache Sedona
  • Cloud infrastructure (GCP preferred), Docker and Git

Outils et compétences

Source et dates

Site carrière / système de candidatures · breezy

Date publiée par l’employeur
2026-02-04
Première détection par notre source
2026-10-14
Mise à jour du dossier source
2026-10-14

Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.

Détails du poste

NiveauIntermédiaire
DomaineDéveloppement logiciel
Expérience4 an(s) et plus
Heures par semaine40 (estimé)
Milieu de travailBureau
PositionSurtout assis
Exigences physiquesphysique faible · ordinateur élevé
LanguesEnglish
FormationBaccalauréat (préféré), Maîtrise (préféré)
Domaines d’étudesGIS, Computer Science, Engineering
Avantages mentionnésHoraire flexible, Actions ou participation

Résumé et détails rédigés par l’IA à partir de l’offre; l’offre de l’employeur fait foi.

Shearwater Aerospace

Profil d’entreprise sauvegardé

Renseignements historiques provenant d’un profil The Jobs API sauvegardé (champs LinkedIn/Crunchbase). Ils ne sont pas vérifiés en temps réel; les chiffres peuvent avoir changé. Les valeurs manquantes restent inconnues.

Personnes associées sur LinkedIn
10
Autres noms enregistrés
  • Shearwater Aerospace
  • Shearwater
ChampValeur
SecteurAviation and Aerospace Component Manufacturing
Siège socialMontreal, Quebec
Offres sur Jobsy1
LinkedInVoir la page
Description

We're Building Autonomous Flight Intelligence

Drones that think for themselves. Not pre-programmed routes—true autonomy where aircraft make intelligent decisions onboard, adapting to weather, obstacles, and airspace in real-time without human intervention.

We're building weather-aware flight optimization that delivers outcome-driven autonomy for the real world—increasing mission success by extending range, endurance, safety, and reliability.

You'll architect the geospatial brain that makes this possible

The Opportunity

You'll be our first geospatial hire, building the data processing systems that enable autonomous flight decisions. Working with our CTO, you'll architect how our systems evolve from initial implementation to production-grade infrastructure that handles real-world operational demands.

Whatyou'll own:

  • Design geospatial processing pipelines that balance performance, accuracy, and extensibility
  • Build GIS analysis algorithms for weather-aware route optimization
  • Integrate multi-source datasets (elevation, obstacles, airspace, meteorological models)
  • Create APIs that enable real-time flight decision-making
  • Establish patterns and tooling that evolve as our platform matures

Why this matters: Operators deploy missions in challenging conditions. Your work directly determines whether autonomous systems can navigate safely, optimize for changing weather, and complete objectives—or get grounded.

You Might Be a Fit If...

You think in trade-offs.
You can explain why you chose PostGIS over alternative spatial databases, or when to pre-process vs. compute on-demand. You know the geospatial database landscape and select tools based on requirements, not trends. You're comfortable defending your decisions and pivoting when new constraints emerge.

You stay current and execute rigorously.
You follow modern geospatial best practices and understand OGC standards. You keep up with evolving tools and approaches instead of relying on outdated tooling.

You've shipped production GIS systems.
You've wrestled with coordinate transformations, spatial indexing, and raster processing. You know the common GIS tools and libraries—GDAL/OGR, various spatial databases, processing frameworks—and understand when each fits. Bonus: you've worked with meteorological data (NetCDF, GRIB) or atmospheric models.

You're comfortable with ambiguity.
Requirements evolve. Priorities shift. You ask clarifying questions, propose solutions, and deliver incrementally rather than waiting for perfect specs.

You communicate clearly.
You can explain technical trade-offs to non-engineers and translate vague product needs into concrete implementation plans. Ego doesn't enter the room when someone questions your approach.

Technical Foundation We're Looking For

Core GIS competency:

  • 4+ years building geospatial software (or 3 years if you've shipped impressive systems)
  • Strong knowledge of common GIS tools and libraries (QGIS, GDAL/OGR)
  • Experience with geospatial algorithms (visibility analysis, spatial operations, terrain analysis)
  • Deep understanding of coordinate systems, projections, and spatial data structures

Python ecosystem:

  • Strong Python with scientific computing stack (NumPy, Pandas, SciPy)
  • Geospatial libraries: GeoPandas, Rasterio, Xarray, Dask

Data infrastructure:

  • Experience with spatial databases (PostGIS, Apache Sedona, etc)
  • Comfortable with cloud infrastructure (GCP preferred), Docker, Git
  • Ability to set up automated data ingestion workflows

Nice to have:

  • C/C++ for performance-critical processing
  • Meteorology, atmospheric science, or aviation background
  • Degree in GIS, Computer Science, Engineering, or related field. Master's is a plus, but we'll prioritize what you've built over credentials.

What We Offer

Equity ownership – You're building foundational systems. You should own a meaningful piece of what we're creating.

Architectural influence – This isn't "implement the spec." You'll shape technical decisions alongside the CTO as we define what autonomous flight infrastructure looks like.

Hybrid flexibility – Work where you're most productive. We're in Montreal but value focus time and thoughtful collaboration over face-time.

Growth with the platform – You'll evolve systems as we mature from initial architecture to production-hardened infrastructure. The foundations you establish will scale with increasing mission complexity, data volumes, and operational demands—and you'll architect that evolution.

Direct impact – Your code runs onboard aircraft making critical flight decisions. You'll see your work enable missions that weren't possible before, extending operational capabilities in real-world conditions.

Apply

We're looking for problem-solvers who thrive when building systems from first principles in a domain that matters.

Strong foundation in geospatial engineering but don't check every box? We want to hear from you. We value learning agility and problem-solving ability over credential collection.

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