Jobber is hiring a Staff Data Engineer in Vancouver!
Jobber is hiring a Staff Data Engineer in Vancouver to join its Data Platform team, with a focus on data integration. This is a senior, hands-on technical leadership role for someone who can architect and build reliable batch and real-time data systems while mentoring engineers and raising engineering standards. The position combines platform design, data governance, observability, self-service tooling, and cross-team collaboration. The engineer will help teams across Jobber access trusted data quickly and will contribute to strategic roadmaps alongside technical program managers and other staff engineers. The listing does not specify a work mode.
Key responsibilities
- Design, build, and maintain scalable batch and real-time data pipelines, anticipating future platform needs.
- Provide technical leadership and mentoring, set engineering best practices, and help team members grow.
- Define reliability standards, SLAs, disaster recovery practices, and lead initiatives that reduce downtime.
- Build observability and governance frameworks for monitoring, logging, lineage, auditing, and data integrity.
- Create self-service tools and automation that make data access easier for engineering, analytics, and data science teams.
- Partner with technical program managers on roadmaps and with technical leaders across domains to improve systems.
- Support analysts, scientists, and product teams with infrastructure that speeds exploration, modeling, and reporting.
- Participate in an on-call rotation and occasional major maintenance work.
Key requirements
- Hands-on data engineering experience with batch and real-time processing, lakehouse or warehouse management, large-scale transformation, orchestration, and dimensional modeling.
- Proven ability to design scalable, maintainable systems using containerization, CI/CD, and API development.
- Strong AWS data-platform experience.
- Demonstrated technical leadership, architecture skills, and high-quality coding with a focus on long-term maintainability.
- Reliability and DevOps background including infrastructure-as-code, observability, and system resilience.
- Excellent communication, self-motivation, and comfort with ambiguity in a fast-paced environment.
- Nice to have: ML platform exposure, distributed compute frameworks, Ruby on Rails or TypeScript/React experience, GraphQL knowledge, platform-building experience, and governance or compliance awareness.
- Seniority: Staff
- Work mode: Not specified
- Salary: Minimum $169,200 CAD; midpoint $199,100 CAD; maximum $228,900 CAD annually
- Key skills: Data Engineering, Batch and Real-time Pipelines, Snowflake, AWS, Data Modeling, Workflow Orchestration, Terraform, CloudFormation, CI/CD, Observability, Data Governance, Mentorship, API Development, Containerization
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