Tech Stack
AirflowAmazon RedshiftAWSCloudDockerJavaScriptKubernetesNode.jsPostGISPythonReactSQLTypeScript
About the role
- Architect Data Systems: Design and implement scalable, secure, and reliable data architectures that support high-volume ingestion, transformation, and analytics
- Build Data Pipelines for AI: Develop robust Airflow-orchestrated pipelines that ingest, transform, and load structured and unstructured agronomic, geospatial, and operational data into Redshift and other data platforms for analytics, BI, and AI/ML-driven applications
- Full Stack Contributions: Contribute hands-on to web applications (React, Node.js) and APIs that deliver data-driven insights to customers and internal teams
- Bridge Data & Applications: Partner with product, data science, and agronomy experts to integrate advanced analytics and predictive models into customer-facing applications
- Elevate Engineering Standards: Establish patterns for data modeling, system design, and code quality; mentor peers and influence engineering best practices
- Stay Ahead of the Curve: Evaluate emerging technologies in cloud computing, data platforms, and AI/ML infrastructure and bring forward innovations that accelerate the mission
Requirements
- 10+ years of experience across software engineering, with significant contributions in both full stack development and data systems
- Proficiency in React, Node.js, and TypeScript/JavaScript
- Expertise in SQL, data modeling, and pipeline orchestration, including hands-on experience with Airflow
- Experience with AWS Redshift (or equivalent cloud data warehouses), including schema design and performance optimization
- Hands-on experience with AWS (preferred), containerization (Docker, Kubernetes), and CI/CD pipelines
- Python proficiency for data engineering and automation workflows
- Geospatial data familiarity (PostGIS, H3, GeoParquet, etc.) is a plus
- Strong problem-solving, collaboration, and mentorship skills