VRIFY is positioned at the forefront of the mining industry's transformation, leveraging cutting-edge AI to revolutionize mineral exploration. With a focus on AI drill targeting, VRIFY is expanding its capabilities by synthesizing vast amounts of geological information. This integration enhances the precision and efficiency of exploration strategies, offering our clients innovative solutions that depart from traditional methods.
VRIFY is seeking an experienced Senior Data System Developer to implement and optimize our geospatial data infrastructure and processing systems under the guidance of our Data Architect. This critical role will translate architectural vision into production-ready systems, focusing on building robust, scalable data pipelines that transform complex geological and geospatial data into valuable analytical assets. You will work closely with our Data Architect to implement data blueprints and standards while collaborating with machine learning engineers and geoscience teams to create efficient data workflows that enable advanced geospatial analytics.
As a Senior Data System Developer, you'll be instrumental in bringing the Data Architect's designs to life through the implementation of modern geospatial data standards, technologies, and processing frameworks. Your expertise in implementing high-performance geospatial data pipelines, spatial data catalogs, and specialized earth observation data formats will be essential in building the foundation for our geospatial AI capabilities.
Key Responsibilities:
Geospatial Data Pipeline Development & Optimization
Implement and maintain scalable ETL/ELT pipelines for processing complex geological and earth observation datasets
Build robust data workflows for standardizing and cataloging geospatial data using industry standards like STAC (SpatioTemporal Asset Catalog)
Develop processing systems for cloud-optimized geospatial formats including GeoParquet, Zarr, Cloud-Optimized GeoTIFF (COG), and GeoJSON
Implement spatial indexing and tiling strategies for efficient geospatial data access and processing
Create data transformation processes for generating ML-ready geospatial training data
Optimize geospatial query performance across distributed datasets
Geospatial Data Infrastructure & Systems
Implement cloud-based geospatial data infrastructure on AWS according to the Data Architect's guidelines
Deploy and configure STAC API services and metadata catalogs for geospatial asset discovery
Implement data lakes optimized for large-scale geospatial data using columnar and chunked storage formats
Configure specialized geospatial databases and services (PostGIS, PgSTAC, GDAL-based systems)
Set up distributed processing frameworks for parallel geospatial analytics
Establish monitoring and performance metrics for geospatial data systems
Data Integration & Spatial APIs
Build data integration frameworks connecting various geological, geophysical, and remote sensing data sources
Implement OGC-compliant web services and APIs for standardized geospatial data access
Develop systems to harmonize data from different coordinate reference systems and projections
Create interfaces between geological databases, GIS systems (ArcGIS, QGIS), and analytics platforms
Implement vector and raster tile services for web-based visualization
Develop automated data ingestion processes for diverse geological and earth observation data formats
Technical Implementation & Support
Implement Data System Developing solutions based on the Data Architect's blueprints and reference models
Provide technical feedback to the Data Architect on implementation challenges and opportunities
Document implemented data flows and prepare technical documentation
Support the Data Architect in technology selection and proof-of-concept development
Ensure implemented solutions conform to established data governance standards
Identify and address technical debt in existing data systems
Cross-team Collaboration
Work closely with the Data Architect to implement architectural designs and patterns
Collaborate with ML engineers to implement geospatial feature stores and training data pipelines
Partner with geospatial scientists to understand specialized data requirements
Support cloud platform engineers with infrastructure optimization for geospatial workloads
Assist data scientists with efficient access to geospatial datasets for analytics
Participate in agile development processes and sprint planning
Required Qualifications
Bachelor’s degree in computer science, Software Engineering, GIS, or related technical field
7+ years of experience in Data System Developing, with at least 3 years focusing on geospatial data systems
Strong expertise in implementing geospatial data pipelines and processing workflows
Experience with cloud-optimized geospatial formats (GeoParquet, Zarr, COG, STAC)
Proficiency in geospatial libraries and tools (GDAL/OGR, Rasterio, GeoPandas, PySTAC)
Extensive experience with AWS geospatial data services and storage solutions
Knowledge of OGC standards and spatial web services
Experience with workflow orchestration tools (Airflow, Step Functions, etc.)
Understanding of coordinate reference systems, projections, and geospatial operations
Ability to work effectively with Data Architects to implement technical solutions
Technical Skills
Geospatial Technologies: STAC, GeoParquet, Zarr, Cloud-Optimized GeoTIFF (COG), GeoJSON
Geospatial Libraries: GDAL/OGR, Rasterio, GeoPandas, PySTAC, Xarray
Programming & Scripting: Advanced Python, SQL, Geospatial Python ecosystems
Data Processing: Apache Spark, AWS Glue, Dask, Pangeo
Spatial Databases: PostgreSQL/PostGIS, PgSTAC
Workflow Orchestration: Apache Airflow, AWS Step Functions
Cloud Platforms: AWS geospatial services, Earth Observation with AWS
Containerization: Docker, Kubernetes
Infrastructure as Code: Terraform, CloudFormation
CI/CD: GitHub Actions, Jenkins
Monitoring: Prometheus, CloudWatch
Additional Skills
Implementer who excels at translating architectural designs into functional systems
Problem solver who thrives on building efficient, scalable geospatial data solutions
Detail-oriented professional with a focus on data quality and spatial accuracy
Collaborative team player who works effectively with architects and technical teams
Self-motivated learner who stays current with emerging geospatial technologies
Practical engineer who balances technical excellence with pragmatic solutions
Resilient troubleshooter who can diagnose and resolve complex geospatial data issues
What We Offer:
Health Benefits: Extensive coverage, medical, dental, and vision plans.
Paid Time Off (PTO): Including vacation days, sick/personal care days, public holidays plus extra time during the holiday season.
Work-Life Balance: Flexible work hours, remote work options plus an option to use workspace in Downtown Vancouver.
Professional Development: Career growth program to help our team advance their careers.
Performance Bonuses
Wellness Programs: Fitness allowance, work-from-home allowance, mental health support.
Retirement Plan (RRSP/DPSP)
Terms of employment:
Full-time, Permanent, Remote work in Canada.
Completion of a background check will be required for this position.
Must be legally entitled to work in Canada.
This job description has been written to provide an accurate reflection of the current job and to include the general nature of work performed. It is not designed to contain a comprehensive detailed inventory of all duties, responsibilities, and qualifications required of the employees assigned to the job. Management reserves the right to revise the job or require that other or different tasks be performed when circumstances change.
We strive to create an environment where every employee feels valued, respected, and empowered regardless of their race, gender, age, religion, identity, or experience. We understand that unique perspectives and backgrounds bring invaluable insights and contribute to the richness of our culture and the effectiveness of our solutions. If you have a disability or any special needs that we might need to accommodate, please let us know.
