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IT/Tech
Data Engineering, Cloud Computing: Infrastructure & Operations, AWS, AI Engineer (Applied/Software)
Job Description & How to Apply Below
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 Big Query, 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.
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