Global Spatial Technology Solutions (GSTS) is a Global Maritime Intelligence company delivering solutions to enhance decision making across the maritime and logistics industry. Our platform, OCIANA, is designed to save lives, energy and the environment on a global scale using innovative data collection and analysis techniques.
GSTS is building a team to support the continued development and commercialization of this capability, which will have a major impact on maritime risk and vessel efficiency on a global scale. We’re seeking individuals with drive, initiative, and adaptability to join our team and make the world safer and greener for all. Read more at: www.gsts.ca

EXPERIENCE & QUALIFICATIONS:

• 10+ years of professional experience in data engineering or platform/backend engineering roles
• Bachelor’s Degree Computer Science, Engineering, related field, or equivalent
• Strong Python and SQL programming skills (PostgreSQL preferred)
• Experience with cloud-native architecture and working with managed services in AWS
• Proven experience in CI/CD, containerization (Docker), and orchestrators like ECS
• Familiarity with Git-based collaboration (GitLab) and Agile/Scrum development environments
• Experience building and optimizing large-scale data infrastructure and distributed systems

ROLE:

As Data Engineer, you’ll play a critical role in building out OCIANA’s geospatial data integrations, enabling real-time decision-making and supporting novel machine learning models. You’ll collaborate with Data Scientists, Product Owners, and Platform Engineers to scale infrastructure, optimize pipelines, and ensure seamless delivery of data services from ingestion to visualization.

KEY RESPONSIBILITIES:

• Architect and maintainData Pipelines and and Data Streams for geospatial and maritime data
• Design and build Data APIs internal and external access (FastAPI)
• Collaborate with Data Scientists to build and deploy ML models using efficient ML OPs practices
• Support and extend CI/CD workflows using GitLab/GitHub and Infrastructure-as-Code (CloudFormation)
• Improve platform observability and reliability
• Support event-driven architecture for scalable data flows across the platform