Data Engineer

Pelmorex•Montreal, QC

12d•Hybrid

About The Position

At Pelmorex, we’re on a mission to transform weather and environmental data into decision-grade insights for businesses and consumers. Our B2B products help organizations make smarter, safer, and more profitable decisions. To support this mission, we’re growing our Engineering Insights team and investing in a scalable data analytics and insights platform. We’re looking for a Data Engineer who enjoys building reliable, scalable data solutions and is passionate about turning raw data into high-quality datasets that power products and business decisions. You will play a key role in building and maintaining the data systems that power multiple B2B products. Your work will directly shape how data is ingested, validated, transformed, and consumed across our B2B product portfolio, ensuring it is reliable, scalable, and decision-ready for our customers. In this role, you’ll collaborate closely with a small, entrepreneurial team of Engineers, Product Managers, and Data Scientists to turn raw data into real-world impact. Please note, we are only considering candidates who are eligible to work in Canada and can work in a Hybrid model at our Oakville or Montreal location.

Requirements

Bachelor’s or Master's degree in Computer Engineering, Software Engineering, Computer Science, or an equivalent technical field.
2-5 years of professional experience in Data Engineering with hands-on experience building and supporting production data systems at scale.
Solid understanding of ETL/ELT patterns, data modeling, partitioning strategies and pipeline design.
Experience deploying, managing, or supporting data workloads in the cloud (GCP preferred).
Strong proficiency in Python and SQL.
Experience writing clean, modular, and maintainable code optimized for heavy data processing.
Strong commitment to automated pipeline testing, continuous integration, comprehensive documentation, and proactive system observability.
Eligible to work in Canada.
Can work in a Hybrid model at our Oakville or Montreal location.

Nice To Haves

Experience working with high-volume geospatial, weather, or time-series datasets.
Familiarity with containerized environments (Docker, Kubernetes) and managing data workloads on cloud compute (e.g., Cloud Run, GKE).
Exposure to infrastructure-as-code principles (e.g., Terraform)

Responsibilities

Develop and maintain ETL/ELT pipelines using modern distributed compute frameworks such as Apache Beam and Snowpark.
Build, monitor, and optimize data workflows using tools like Apache Airflow, Google Workflows, and Snowflake Tasks.
Implement and optimize data models and storage across BigQuery, Snowflake, PostgreSQL, and Google Cloud Storage to ensure scalable and efficient data solutions.
Implement robust data validation frameworks, write unit/integration tests for data pipelines, establish CI/CD, and set up proactive monitoring for data integrity and system health.
Help improve data system performance, reduce costs, and increase reliability.
Partner with Engineers, Product Managers, and Data Scientists to deliver high-quality data solutions that support business needs.