Staff Data Engineer

Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move.

Salary: CAD 169,200–228,900 / yr

Department: Data Science & Analytics

Employment: Full Time

Experience: Director

Published: 9 Oct 2026

Apply before: 8 Nov 2026

Jobber is hiring a Staff Data Engineer for its Data Platform/Data Integration team to build foundational data movement, transformation, and self-service capabilities. The role combines hands-on architecture and coding with technical leadership, mentorship, and cross-functional roadmap work. Core responsibilities include scalable batch and real-time pipelines, Snowflake CDC materialization, data governance, observability, reliability standards, and disaster recovery. The engineer will participate in an on-call rotation and partner closely with engineering, analytics, data science, product, and program-management stakeholders.

This is a staff-level platform role requiring deep expertise across distributed data systems, cloud infrastructure, reliability engineering, governance, and software architecture. The successful candidate must independently influence technical direction while leading high-impact initiatives across multiple teams.

The Data Integration team’s mission is to empower teams across Jobber with the right data, at the right time, in the right place, so they can deliver business value better and faster. Key responsibilities include:

• Data ingestion and Change Data Capture (CDC), including materializing CDC streams into tables in Snowflake
• Data activation (egress)
• Managing the systems involved in the movement and transformation of data
• Self-serve tooling
• Data integrity and governance

As a Staff Data Engineer, you will play a critical role in shaping the future of data integration at Jobber. Your expertise will span architecture, technical leadership, design, and hands-on coding, enabling you to significantly influence the direction of data at Jobber. Beyond day-to-day delivery, you will dedicate time to work acceleration, cross-team initiatives, exploration of emerging technologies, addressing technical debt, and investing in the future of engineering at Jobber.

To be successful, you should have:

• Core Data Engineering Expertise: Hands-on experience with batch and real-time data processing frameworks, lakehouse/warehouse management, large-scale data transformation, data serialization, workflow orchestration and dimensional modeling (star/snow-flake schemas)
• Scalable Systems Development: Proven ability to design and deliver highly scalable, maintainable, and high-performance solutions across multiple layers of the technology stack, leveraging containerization, CI/CD, and API development.
• AWS Cloud Proficiency: Strong understanding of AWS services relevant to the data domain, with hands-on experience leveraging them to design and implement data solutions.
• Technical Leadership & Engineering Excellence: Demonstrated success guiding teams through complex, high-impact projects while providing architectural direction and serving as a trusted technical lead.
• Reliability & DevOps Practices: Strong background in infrastructure-as-code (Terraform, CloudFormation), observability (logging, monitoring, tracing), and system reliability.
• Collaboration & Adaptability: Exceptional communication skills, self-motivation, and resourcefulness, with the ability to navigate ambiguity, prioritize effectively, and deliver results in fast-paced environments.

It would be really great (but not a deal-breaker) if you had:

• Machine Learning Platform Experience: Exposure to ML platforms and distributed compute frameworks (e.g., Ray, TensorFlow, PyTorch).
• Cross-Domain Engineering Experience: Hands-on exposure to non–data engineering codebases, such as web application frameworks (Ruby on Rails) and modern front-end stacks (TypeScript/React).
• API & Integration Knowledge: Familiarity with GraphQL, API layer design, and performance optimization.
• Platform Building Experience: Prior work on developer tooling or shared platforms that supported multiple engineering domains.
• Governance & Compliance Awareness: Knowledge of data privacy, security, and compliance in cloud-based data environments.

At Jobber, we also believe that compensation should be transparent, fair, and supportive of your experience and growth. This role has a minimum annual salary of CAD 169,200, a midpoint of CAD 199,100 and a maximum salary of CAD 228,900, designed to reflect the progression from learning the ropes to truly excelling.

We believe in transparency and open conversations about compensation. If you have any questions about our approach, we’re happy to discuss them throughout the hiring process!

We believe that diverse teams perform better and that fostering an inclusive work environment is a key part of growing a successful team. We welcome people of diverse backgrounds, experiences, and perspectives. We are an equal opportunity employer, and we are committed to working with applicants requesting accommodation at any stage of the hiring process.