Cloud Data Engineer — AI-Ready Pipelines & Impact

Semios; Vancouver; Hybrid; CAD 133,000 - 161,000; Full time

Benefits offered by this job

Group RRSP with 3% company match

Hybrid work arrangements

Health plans

Job summary

Semios is seeking a Data Engineer to design, build, and maintain scalable cloud-based data systems that transform raw data into trusted, analysis-ready datasets. You will collaborate with Engineering and Data Science teams to optimize data pipelines and integrate diverse data sources for AI-ready foundations powering agriculture products.

Ideal candidates have 3–5 years in data engineering, strong SQL, and experience with data warehouses (BigQuery, Redshift, Snowflake) and Postgres, plus

Qualifications

• 3–5 years of professional experience in Data Engineering.
• Advanced SQL skills.
• Experience with at least one Data Warehouse (BigQuery, Redshift, Snowflake or an on-prem equivalent) and with Postgres or another relational database.
• Experience with cloud platforms (GCP and AWS).
• Experience with Prefect or Dagster or similar.
• Fluency in Python, Node or other imperative language.

Responsibilities

• Architect and build cloud-based data 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.
• Model large, complex datasets that meet business and product requirements.
• Optimize pipeline performance and cost 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.

Skills

SQL

Python

GCP (BigQuery, Cloud Run)

AWS

Prefect

Dagster

dbt

Data pipelines

Communication skills

Education

Advanced education in Big Data

Tools

BigQuery

PostgreSQL

Job description

Semios is seeking a Data Engineer to design, build, and maintain scalable cloud-based data systems that transform raw data into trusted, analysis-ready datasets. You will collaborate with Engineering and Data Science teams to optimize data pipelines and integrate diverse data sources for AI-ready foundations powering agriculture products.

Ideal candidates have 3–5 years in data engineering, strong SQL, and experience with data warehouses (BigQuery, Redshift, Snowflake) and Postgres, plus