Overview
Senior Data Engineer responsible for building scalable data platforms, pipelines, distributed processing workflows, and AI-enabled tooling for analytics and data engineering.
What you'll do
- Develop end-to-end data pipelines and backend ingestion workflows.
- Integrate and transform ERP, CRM, product, order flow, and support data.
- Build and optimize Spark and PySpark batch and streaming workflows.
- Improve data architecture, quality, monitoring, observability, and availability.
- Build MCP servers and integrate agentic workflows into data engineering.
- Lead projects and provide technical guidance and mentorship.
What you'll need
- Bachelor's degree in computer science, data engineering, data science, information technology, or an equivalent engineering program.
- 8+ years of experience as a software engineer with a data focus or as a data engineer.
- 5+ years building production-grade data pipelines, including data modeling.
- 5+ years of hands-on production Spark or PySpark experience.
- Strong Python and SQL programming skills.
- Experience with cloud data warehouses or lakehouses and cloud platforms.
- Experience with APIs, RDBMS platforms, and ETL tools.
Nice to have
- Experience designing a centralized semantic layer.
- Experience with Splunk, DataDog, AWS CloudWatch, or equivalent.
- Experience with AWS serverless services.
Details
- Remote position open to candidates residing in Canada.
- Annual base salary: CAD 119,000–154,000.
- Employment type: full-time.
Read the full description and apply on the company’s own careers page.
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