Spatial Platform Tech Lead

Your Team Responsibilities

The Spatial Platform team is responsible for developing and maintaining a scalable data processing platform that leverages spatial attributes to manage asset data. Built on a medallion architecture, the platform supports high-volume concurrent processing and enables the creation of refined data products like GSAI.

Key responsibilities include:

• Ingesting and enriching data from multiple sources, with rigorous quality checks to ensure data integrity.
• Building RESTful microservices using Python FastAPI, with automated testing via pytest integrated into CI/CD pipelines.
• Conducting performance and security testing to ensure the platform is robust, scalable, and secure.
• Maintaining detailed documentation on Confluence and collaborating with stakeholders to align with business goals.
• Supporting the development and delivery of high-quality data products for internal and external clients.
• Ensuring code quality through tools like SonarQube, targeting 90%+ test coverage.

Your Key Responsibilities

As a Tech Lead, you will play a pivotal role in driving the technical direction and execution of the Spatial Platform. Your responsibilities will include:

• Guiding the migration of legacy modelling code to the Spatial Platform, ensuring scalability and performance.
• Designing and enhancing platform capabilities to support processing of millions of assets using spatial attributes.
• Collaborating closely with researchers to enable model development and experimentation directly within the platform.
• Overseeing the development of microservices and ensuring best practices in testing, deployment, and monitoring.
• Leading performance tuning, security hardening, and production readiness efforts.
• Establishing and enforcing architectural standards, code quality, and documentation practices.
• Mentoring engineers, conducting code reviews, and fostering a culture of technical excellence and continuous improvement.

Your skills and experience that will help you excel

• Strong proficiency in Python, with experience in building scalable microservices using FastAPI or similar frameworks.
• Solid understanding of data engineering principles, including data ingestion, enrichment, and quality validation.
• Hands-on experience with CI/CD pipelines, pytest, and SonarQube for automated testing and code quality.
• Familiarity with medallion architecture and concurrent data processing at scale.
• Experience with performance and security testing in production-grade systems.
• Excellent problem-solving skills and the ability to translate business needs into technical solutions.
• Strong communication and collaboration skills, with experience working across cross-functional teams.
• Prior experience in a technical leadership or mentorship role is a plus.