Senior Data Engineer - Hybrid

Pelmorex•Montreal, QC

21h•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 doesn’t just move data, but understands how data quality, latency, and design decisions directly impact products, customers, and business outcomes. You will play a foundational role in architecting and building the data systems and analytics capabilities 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

5+ years of professional experience in Data Engineering and Backend Engineering with demonstrated ownership of production systems.
Deep understanding of ETL/ELT patterns, data modeling, partitioning strategies, idempotent pipeline design, and cost-aware storage design and compute optimization.
Experience designing and building RESTful APIs, handling authentication and authorization, and optimizing queries across relational and NoSQL databases.
Proven ability to deploy and manage production workloads in the cloud (e.g., GCP) including a solid grasp of IAM, managed services, serverless, and containerized compute.
Proven ability to lead design discussions, influence technical direction, mentor teammates, and collaborate effectively with cross-functional partners.
Strong commitment to code and data quality, unit/integration testing, CI/CD, documentation, and owning systems from development to production support.

Nice To Haves

Experience with supervised/unsupervised learning, feature engineering, distributed training and serving models at scale.
Familiarity with cloud networking, VPC design, security best practices, and infrastructure-as-code (e.g., Terraform).

Responsibilities

Architect for Scale: You'll define the blueprints for high-scale systems where quality and latency are the primary constraints.
Build the Backbone: You will engineer robust pipelines using a cutting-edge stack including Ray, Snowpark, and Apache Beam.
Master Workflow Orchestration: You will design and operate sophisticated workflows and intelligent scheduling strategies leveraging Apache Airflow, Snowflake Tasks, and Google Workflows.
Power Data Access: You will design and build scalable backend APIs and services in Node.js and Python to deliver reliable, well-defined data to internal and external systems.
Optimize Global-Scale Storage: You will design and fine-tune high-performance storage solutions across BigQuery, Snowflake, PostgreSQL, Cloud Spanner, and GCS, optimizing for cost, performance, and reliability.
Own Production Systems: You will build CI/CD pipelines, implement observability and monitoring, and own production systems to ensure data integrity and platform health.