Staff Data Engineer

About the role

The Staff Data Engineer will lead and mentor a team of data engineers while shaping the future of data integration at Jobber. This role involves designing resilient systems, driving technical excellence, and empowering teams across the organization to work effectively with data. You will combine deep technical expertise with leadership to ensure data remains a trusted asset that accelerates business growth.

Responsibilities

• Design, build, and maintain scalable batch and real-time data pipelines.
• Champion technical excellence by setting best practices and mentoring team members.
• Establish testing and reliability standards, SLAs, and disaster recovery playbooks.
• Build frameworks for monitoring, logging, lineage, and auditing to ensure data trust.
• Develop self-service tools and automation to reduce manual effort and improve efficiency.
• Partner with technical leadership to define strategic roadmaps and align priorities with business objectives.
• Collaborate across domains to identify friction points and design scalable solutions.

Required skills

• Data Engineering
• Batch processing
• Real-time data processing
• Data warehousing
• Data transformation
• Data serialization
• Workflow orchestration
• Dimensional modeling
• AWS
• Infrastructure-as-code
• Terraform
• CloudFormation
• Observability
• System architecture

Nice to have

• Machine Learning platforms
• Ray
• TensorFlow
• PyTorch
• Ruby on Rails
• TypeScript
• React
• GraphQL
• Data privacy
• Security compliance

Benefits

• Extended health benefits
• Retirement savings matching
• Stock options
• Annual health and wellness stipend
• Career coaching
• Talent development program

About the Company

Jobber helps small home service businesses transform the way service is delivered through technology, enabling them to quote, schedule, invoice, and collect payments. The company has been recognized for its culture and growth by organizations including Great Place to Work and Deloitte.