Who we are 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. The Semios Group includes trusted brands such as Semios, Agworld, Altrac, and Greenbook. We continue to drive the next generation of digital agriculture, supporting growers, agronomists and ag retailers in improving sustainability and profitability.

Who we are 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. The Semios Group includes trusted brands such as Semios, Agworld, Altrac, and Greenbook. We continue to drive the next generation of digital agriculture, supporting growers, agronomists and ag retailers in improving sustainability and profitability.

AgTech Breakthrough - Smart Irrigation Company & Pest Management Solution of the Year

Thrive Top 50

Google for Startups Accelerator Cohort

Global Cleantech Top 100

We know our journey is only achievable by having a great team who shares ideas, tries new things, and learns as we go.

Who you are 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.

What you will do

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 innovative industry leader

Model large, complex datasets that meet business and product requirements

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 transparent documentation of data structures and Data APIs across products

Requirements

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

Excellent verbal and written communication skills: a talent for distilling complex ideas for different audiences

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

Proven experience with workflow and scheduling tools like Prefect, Dagster or similar

The ability to thrive both autonomously and in a team environment

Excellent troubleshooting skills to rapidly identify and resolve issues

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

Nice to have

Real‑world experience with containers (Docker) & container management systems (Kubernetes)

Experience with IoT data: ingesting and processing time‑series sensor dat

📌 Data Engineer (Winnipeg)
🏢 Semios Group
📍 Winnipeg