Responsibilities
- Architect, design, and maintain robust, scalable data pipelines and infrastructures for geospatial and big data applications maintaining a focus on performance and the ultimate end-user product experience.
- Lead the development and optimization of ETL processes for ingesting, cleaning, transforming, and storing large volumes of geospatial and tabular data.
- Design, build, and interact with API-driven, service-to-service web services (using FastAPI, Litestar, Flask, etc.) to enable integration across a suite of products.
- Collaborate with backend and platform engineers to ensure secure, reliable, and scalable service-to-service communication.
- Translate complex analytics and business questions into actionable, production-grade data solutions.
- Collaborate closely with data scientists, analysts, and business stakeholders to deliver high-impact data products.
- Drive the adoption and optimization of cloud-based data solutions (e.g., GCP, AWS, Azure).
- Ensure data quality, integrity, and security across all stages of the data lifecycle.
- Mentor and provide technical guidance to junior data engineers and team members.
- Communicate technical details and insights clearly to both technical and non-technical audiences, including leadership.
- Proactively recommend and implement improvements to existing data infrastructure and software programs.
- Stay current with industry trends and emerging technologies in geospatial data engineering.
