Data Engineer

Semios

. Architect and build cloud-based systems managing and improving the interface between Semios data and its consumers .

Posted 10/31/2026full-timeVancouver • CanadaMid-LevelSenior💰 CA$95,000 - CA$115,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in architecting and building cloud-based data systems, optimizing data pipelines, and integrating data-driven models. Proficient in SQL, Python, and cloud platforms like GCP and AWS, with a strong focus on data engineering best practices.

Highest-signal resume keywords

Cloud-Based Data EngineeringAdvanced SQL SkillsProduction Data PipelinesGCP and AWS ExperienceData Warehouse Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLPythonData Pipeline DevelopmentData ModelingData IngestionData TransformationCloud InfrastructureWorkflow ToolsMonitoring and Fault-ToleranceData Governance

Soft Skills

Excellent Communication SkillsTroubleshooting SkillsTeam CollaborationAutonomous Work Ability

Tools & Technologies

BigQueryRedshiftSnowflakePostgresDbtPrefectDagsterDockerKubernetes

Certifications & Qualifications

Big Data Certifications

Industry Keywords

Data EngineeringCloud PlatformsData ScienceAnalyticsIoT Data Processing

Tech Stack

Tools & technologies

Amazon RedshiftAWSBigQueryCloudDockerGoogle Cloud PlatformIoTKubernetesNode.jsPostgresPythonSnowflakeSQL

About the role

Key responsibilities & impact

Architect and build cloud-based systems managing and improving the interface between Semios data and its consumers
Design, develop, and maintain scalable infrastructure for processing and storing data
Integrate data-driven models and automate manual processes
Build and maintain models transforming raw measurements into trusted, analysis-ready datasets in a multi-cloud environment
Design and build reliable, monitorable, and fault-tolerant data systems and processes
Create data tools for analytics and data science teams
Model large, complex datasets according to business and product requirements
Optimize pipeline performance and cost through partitioning, clustering, and incremental models
Lead refactoring and migrations
Prepare well-modeled, documented, and governed datasets for LLM-based agents, analytics assistants, and ML models
Build and maintain ingestion pipelines from third-party and partner APIs
Document data structures and Data APIs across products
Collaborate with Engineering and Data Science teams to support agriculture products and data-driven insights

Requirements

What you’ll need

3–5 years of relevant professional experience in Data Engineering, preferably with cloud-based data platforms and production data pipelines
Advanced SQL skills, including minimizing data processing, scanning, and latency
Experience with at least one data warehouse: BigQuery, Redshift, Snowflake, or an on-premises equivalent
Experience with Postgres or another relational database
Excellent verbal and written communication skills
In-depth experience building and operating production data pipelines at scale
Hands-on experience provisioning and developing on cloud platforms, particularly GCP (BigQuery, Cloud SQL, Cloud Run) and AWS
Experience with workflow and scheduling tools such as Prefect, Dagster, or similar
Ability to work autonomously and in a team environment
Excellent troubleshooting skills
Production experience with dbt or a similar SQL-based transformation tool
Experience integrating AI assistants into development workflows
Fluency in Python, Node, or another imperative language
Nice to have: Docker and Kubernetes experience
Nice to have: IoT data ingestion and processing experience
Nice to have: experience building LLM-based agents and AI agents for customer-facing analytics
Nice to have: advanced education in Big Data or relevant certifications

Benefits

Comp & perks

Generous vacation policy
Company-paid holidays
Year-end winter break
Hybrid working arrangements
Strong work-life balance culture
Comprehensive health plans supporting physical and mental health
Group RRSP with a 3% company-paid match after three months of employment
Office location convenient via transit and bike paths
Interview accommodations available upon request