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.

📌 Cloud Data Engineer AI Foundations (Winnipeg)
🏢 Semios
📍 Winnipeg