Data Engineering Lead (Montreal)
US Mobile
Software Engineering, Data Science
Montreal, QC, Canada
CAD 175k-225k / year
US Mobile is building the future of wireless communication. The goal: one unified network open to any person and any device, worldwide. Connection without walls.
We’re getting there by empowering customers. All three major networks on one phone and one plan, plus home internet from Starlink. No lock-in. No commitments. Custom fit plans at every price point. 24/7 customer support with real people, empowered to help. We get real-time feedback from Reddit, surveys, and customer support informing product roadmaps and everything we do. It’s working — Consumer Reports named us the top-rated mobile carrier two years in a row.*
And we’re building innovative systems that scale. A network agnostic tech stack. Agile, cross-functional teams built on trust and mutual respect. This work isn’t for everyone. If you work fast, flexibly, and collaboratively — without compromising standards — we want to hear from you.
Key Responsibilities
- Architect Scalable Systems: Design and maintain robust data pipelines, ETL/ELT processes, and data models supporting analytics, ML, and BI tools.
- Modern Data Stack Ownership: Oversee and optimize tools across the stack — e.g., S3, Redshift, Snowflake, BigQuery, etc.
- Data Quality & Governance: Implement strong data validation, observability, and governance practices to ensure trust and compliance.
- Collaboration: Partner with analytics, product, and engineering teams to define data requirements and improve data usability across the organization.
- Performance Optimization: Continuously enhance system efficiency, scalability, and cost-effectiveness.
- Strategic Input: Influence the long-term data strategy — infrastructure modernization, data platform evolution, and cloud architecture.
Qualifications
- 6+ years of experience in data engineering, including 2+ years in a leadership or team lead role.
- Proven experience designing and maintaining scalable data pipelines, ETL/ELT processes, and data models for analytics, ML, and BI.
- Hands-on expertise with modern data stack tools such as S3, Redshift, Snowflake, and BigQuery.
- Deep understanding of SQL, Python, and ETL frameworks, as well as data quality, validation, observability, and governance best practices.
- Deep knowledge of cloud infrastructure, data architecture, and performance optimization.
- Strong communication and leadership skills, with the ability to guide both strategy and execution.
Benefits
- Competitive salary 175k CAD - 225k CAD (based on experience)
- Flexible working hours
- Supplemental health insurance
- Professional development stipend
- $500 wfh tech set-up reimbursement
175000 - 225000 CAD a year