Failure analysis engineer Jobs in Vancouver, BC

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.

Our innovative work has been recognized with several industry awards, including:

• 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 clear documentation of data structures and Data APIs across products.

Requirements

We want you to succeed, so you will need:

• 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 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.
  

Salary range: $95,000 to $115, 000 per year

We publish a salary range to provide transparency and represent the full growth potential of the role; as a result, offers are made based on demonstrated mastery and experience and generally fall near the midpoint.

Benefits

Why this is the opportunity for you:

• Purposeful Work: Make a global impact by advancing sustainable food production.
• Our People: Work with a fun, collaborative, and supportive team.
• Recharge: Generous vacation policy, company-paid holidays and year-end winter break.
• Work Flexibility: Hybrid working arrangements and strong work-life balance culture.
• Prioritize Your Well-Being: Access comprehensive health plans designed to support your physical and mental health.
• Group RRSP, which includes a 3% company paid match after three months of employment
• Office location that is convenient via transit and bike paths

At Semios Group, we value the full range of experience and perspectives people bring—not just what’s listed in a job description. If your background is a close match, we encourage you to apply. If you need accommodations during the interview process, please let us know.

We welcome all applicants regardless of race, gender, orientation, sexual identity, economic class, ability, disability, age, religious beliefs or disbeliefs, or status. We believe that different perspectives and backgrounds are what make a company flourish.