Cloud Data Engineer AI Foundations

Build scalable cloud data systems at Semios, using advanced SQL and Python to create trusted datasets for agricultural technology products.

As a Data Engineer, you will design, develop, and maintain production data pipelines across multi-cloud environments. You will collaborate with Engineering and Data Science teams while integrating diverse sources, optimizing infrastructure, and creating AI-ready data foundations. Your work will support analytics, machine learning, and data-driven agricultural insights.

Key Responsibilities:

• Architect cloud systems connecting Semios data with consumers
• Build scalable infrastructure for processing and storing data
• Develop models turning raw measurements into trusted datasets
• Optimize pipeline performance, cost, migrations, and refactoring
• Document data structures and Data APIs across products

Requirements:

• Three to five years of relevant Data Engineering experience
• Advanced SQL and production pipeline development skills
• Experience with BigQuery, Redshift, Snowflake, or equivalents
• Cloud experience, particularly GCP and AWS platforms
• Fluency in Python, Node, or another imperative language

Shape Semios data platforms through cloud engineering, advanced SQL, reliable pipelines, and AI-ready dataset development.