Senior Staff GIS Engineer

NBCUniversal•New York, NY

4d•$175,000 - $210,000•Remote

About The Position

In this role, you will serve as a senior technical leader for the geospatial data and tooling capabilities that support a large-scale project. You will set technical direction for how geospatial data is sourced, evaluated, prepared, and delivered through AI/ML pipelines, while solving the organization’s most complex GIS engineering challenges. You will work across imagery and other raster data, vector data, point clouds, and terrain and land-cover datasets. You will define scalable approaches for acquiring data from open, public-domain, and commercial sources, and you will help shape strategic partnerships with data providers. You will establish standards for coverage, freshness, quality, provenance, licensing, and cost so that geospatial datasets can be used reliably at scale. You will architect and evolve automated systems that clean, validate, resize, reformat, align, and postprocess geospatial data for internal AI/ML and product teams. Using open-source technologies such as GDAL and PROJ, along with internally developed tools, you will guide the development of durable, observable, and reusable workflows rather than one-off processing solutions. This is a highly cross-functional individual contributor role. You will partner with AI/ML, Pipeline, Product, and leadership teams to translate product vision into a long-term geospatial data strategy. You will also provide technical mentorship, raise engineering standards, lead design reviews, and influence decisions across teams without relying on direct authority.

Requirements

Master's degree in GIS, Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience.
8+ years of relevant industry experience, including substantial experience designing and delivering production geospatial data systems in a fast-paced technology environment.
Demonstrated technical leadership across complex, cross-functional initiatives, including setting architecture, influencing technical direction, and driving work through ambiguity.
Deep knowledge of geospatial modalities, formats, coordinate systems, and processing techniques, including experience with several of the following: raster data such as orthoimagery, landcover, DTM, DSM, and DEM data, stored as GeoTIFFs, JPEGs, or other formats; point clouds, including LiDAR-sourced point clouds stored in LAS/LAZ and other formats; vector data of diverse types stored in formats such as Shapefile, GeoJSON, and OSM.
Strong software engineering and system design experience, including architecture for scalable, maintainable, and automated data-processing systems.
Advanced Python experience for production automation, data processing, tooling, testing, and integration with existing software systems.
Experience assessing geospatial data quality, coverage, provenance, licensing constraints, and fitness for downstream technical use.
Ability to communicate technical strategy and tradeoffs effectively with engineering, research, product, and senior leadership audiences.
Experience applying a forward-looking but carefully considered integration of LLM-assisted development tools into a Geospatial Engineering workflow, where appropriate.

Nice To Haves

Deep experience with open-source geospatial libraries and tools, including GDAL and PROJ, for spatial data processing, transformation, and analysis.
Comfort working outside an ArcGIS-centric workflow and selecting fit-for-purpose open-source technologies.
Experience with Linux and shell environments such as bash.
Experience building cloud-based or distributed data-processing workflows for large geospatial datasets.
Familiarity with data catalogs, lineage, metadata, validation frameworks, monitoring, and operational support for production pipelines.
Experience supporting geospatial data used in machine learning, computer vision, simulation, digital twins, or large-scale interactive applications.
A collaborative, low-ego approach to technical leadership, with a demonstrated ability to mentor others and build alignment across disciplines.
Passion and curiosity for GIS, software engineering, automation, and emerging GeoAI methods.

Responsibilities

Own the technical strategy and architecture for sourcing, preparing, validating geospatial datasets across target regions.
Lead the resolution of ambiguous, high-impact GIS engineering problems that span multiple data modalities, systems, and teams.
Define standards and measurable controls for data coverage, freshness, quality, provenance, licensing, reliability, and cost.
Evaluate open, public-domain, and commercial sensor data sources, and provide technical leadership for provider selection and data partnerships.
Architect scalable geospatial processing systems using open-source and internally developed tooling to align, crop, resample, transform, validate, and otherwise prepare data for use.
Design and guide automated postprocessing workflows for the outputs of geospatial AI/ML pipelines, with attention to performance, repeatability, observability, and maintainability.
Make meaningful hands-on contributions to internal software and tools used to source, process, catalog, and distribute geospatial datasets.
Partner with AI/ML teams to anticipate model-development data needs and ensure access to diverse, representative, and fit-for-purpose datasets.
Partner with Pipeline and Product teams to define data requirements, technical interfaces, quality thresholds, and launch-readiness criteria for new regions and capabilities.
Lead technical design reviews and drive alignment on architecture, tradeoffs, sequencing, and risk across partner teams.
Mentor engineers, share domain expertise, and establish engineering practices that improve the quality and velocity of the broader GIS function.
Communicate complex technical decisions, dependencies, and risks clearly to engineering leaders, product partners, and other stakeholders.
Partner closely with leadership to connect the long-term product vision to an actionable geospatial data and technology roadmap.