Kevin Lacaille
Data Engineer
Vancouver, British Columbia, Canada
Summary
👤
Senior🎓
Top SchoolKevin Lacaille is a data engineer specializing in cloud-native geospatial pipelines for imagery, point clouds, and video, with nine years of experience building scalable systems from sensor to product. He has shipped production photogrammetry and image-processing pipelines, georeferencing algorithms, and buyer-facing APIs at companies like Spexi and Planet, and now applies those skills at Atomic Maps. Kevin blends research-grade signal and astrophysical image processing with practical ML and CV—having led algorithm work on infrared tracking systems and contributed coastline recession analysis notebooks to Planet’s popular open-source collection. His stack spans Python, TypeScript, Postgres/PostGIS, AWS, and modern ML frameworks, and he’s delivered NeRF/Gaussian splatting and point-cloud workflows for 3D reconstruction. He’s equally at home authoring SDKs and CLIs for developer ecosystems as he is optimizing large-scale data ingestion and synthetic-data generation pipelines. Based in Vancouver, he combines a physics/astronomy background with hands-on engineering to turn complex geospatial data into usable products.
8 years of coding experience
8 years of employment as a software developer
PhD (self-withdrew) Astronomy and Astrophysics, PhD (self-withdrew) Astronomy and Astrophysics at McMaster UniversityMSc Physics, MSc Physics at Dalhousie University
English, French
Stackoverflow
26reputation
1kreached
1answer
0questions
Github Skills (12)
computer-vision10
jupyter-notebook10
opencv10
sens10
rasterio10
python10
image-processing10
numpy10
data-analysis10
matplotlib9
matlab6
interpolation6
Programming languages (6)
Github contributions (5)
planetlabs/notebooks
Aug 2021 - Jan 2023
interactive notebooks from Planet Engineering
Role in this project:
Data Scientist
Data ScientistContributions:41 reviews, 40 commits, 11 PRs in 1 year 5 months
Contributions summary:Kevin contributed to a workshop on coastline recession analysis. They developed and implemented a complete image processing pipeline to measure coastline changes using remote sensing data. Their code included functions for extracting spectral bands, composing scenes, calculating the Normalized Difference Water Index (NDWI), and applying morphological filters to create water and land masks. They also implemented code to measure the area of land lost over time and visualize the coastal changes.
apidata-analysispythonsatellite-imageryplanet
kevinlacaille/LeetCode-practice-problems
Apr 2019 - Aug 2020
Contributions:59 commits, 65 pushes, 3 branches in 1 year 4 months
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