Founded in 2010, Semios Group is a leading agricultural technology company helping growers, agronomists, and ag retailers manage over 200 million acres across five countries. Semios pioneered variable-rate pheromone-based mating disruption in orchards and has since expanded into a comprehensive portfolio covering crop protection, water management, frost control, automation, and a leading farm management information system. We continue to drive the next generation of digital agriculture, supporting growers, agronomists and ag retailers in improving sustainability and profitability. As a Data Engineer at Semios, you will design, build, and maintain scalable, reliable cloud-based data systems that transform raw data into trusted, analysis-ready datasets. You will work closely with our Engineering and Data Science teams to optimize data pipelines, integrate diverse data sources, and build AI-ready data foundations that power innovative products and data-driven insights for agriculture. Help architect and build cloud-based systems to manage and improve the interface between Semios data and its consumers. Design, develop and maintain scalable infrastructure to process and store data, integrate data-driven models and automate manual processes. Build and maintain models that turn raw measurements into trusted, analysis-ready datasets in a multi-cloud environment. Design and build reliable, monitorable and fault-tolerant data systems and data processes. Create data tools for analytics and data science team members that assist them in building and optimizing our product into an creative industry leader. Optimize pipeline performance and cost (partitioning, clustering, incremental models), and lead refactoring and migrations. Make our data AI-ready: well-modelled, documented and governed datasets that power LLM-based agents, analytics assistants and ML models.



Build and maintain ingestion pipelines from third-party and partner APIs. Write clear documentation of data structures and Data APIs across products. 3–5 years of relevant professional experience in Data Engineering, preferably working with cloud-based data platforms and production data pipelines. Advanced skills in SQL; how to write elegant queries that minimize data processing, scanning, and latency. Experience with at least one Data Warehouse (BigQuery, Redshift, Snowflake or an on-prem equivalent) and with Postgres or another relational database. In-depth experience building and operating production data pipelines at scale, with a track record of reliable collection, storage and access. Hands-on experience with provisioning and developing on cloud platforms, particularly GCP (BigQuery, Cloud SQL, Cloud Run) and AWS. Experience with dbt (or a similar SQL-based transformation tool) in production. Experience integrating AI assistants into your development workflow, and a thoughtful view on where they speed things up and where they need close supervision. Fluency in Python, Node or other imperative language. Experience with IoT data: ingesting and processing time-series sensor data from field devices in the cloud. Experience building LLM-based agents to aid development and deployment, and AI agents for customer-facing data analytics. Advanced education in Big Data, whether from academia, or certifications. Purposeful Work: Make a global impact by advancing sustainable food production. Generous vacation policy, company-paid holidays and year-end winter break. Prioritize Your Well-Being: Access comprehensive health plans designed to support your physical and mental health. Office location that is convenient via transit and bike paths We welcome all applicants regardless of race, gender, orientation, sexual identity, economic class, ability, disability, age, religious beliefs or disbeliefs, or status.

📌 Data Engineer (Winnipeg)
🏢 Semios
📍 Winnipeg