Note: The job is a remote job and is open to candidates in USA. Jobber provides technology that helps small home service businesses manage quoting, scheduling, invoicing, payments, and customer experiences. The Staff Data Engineer will lead and mentor data engineers while designing resilient batch and real-time data systems, advancing data integration, governance, reliability, observability, and self-service capabilities across the organization.
Responsibilities
- Shape Foundational Data Components: Design, build, and maintain scalable batch and real-time data pipelines, while also looking across systems and ahead to anticipate future needs
- Demonstrate Technical Mastery: Deliver high-quality solutions through deep expertise in modern data tools and technologies. Champion technical excellence within the team by setting best practices, raising the bar for engineering quality, and mentoring team members at all levels to support their growth and career development
- Drive Reliability & Resilience: Establish testing and reliability standards, SLAs (uptime, RTO, RPO), and disaster recovery playbooks. Lead major reliability initiatives to minimize downtime and protect critical business data
- Advance Observability & Governance: Build frameworks for monitoring, logging, lineage, and auditing to ensure visibility, compliance, and trust in data. Define governance policies that enforce data integrity, availability, and reliability across the platform
- Accelerate and Empower Data Access: Develop self-service tools, frameworks, and automation that reduce manual effort, improve efficiency, and enable teams across engineering, analytics, and data science to work effectively with data while minimizing dependency on the Data Platform team
- Contribute to Strategic Planning: Partner with Technical Program Managers to define and refine strategic roadmaps, ensuring that data engineering priorities align with business objectives
- Drive Cross-Team Collaboration: Collaborate with Staff Engineers and technical leaders across domains to identify friction points, and work collectively to design solutions that improve system reliability, consistency, and scalability
- Accelerate Business Growth: Work closely with data analysts, scientists, and product teams to enable fast, seamless exploration, analysis, modeling, and reporting. Build automation and infrastructure that reduce friction and accelerate decision-making
- Safeguard Data Integrity: Own the integrity and reliability of data, ensuring stakeholders across the organization maintain trust in the insights and decisions driven by it
- On-Call Rotation: Members of the Data Platform team participate in an on-call rotation, covering one week at a time. When an incident occurs outside of regular working hours, we provide time off in lieu to support healthy balance and recovery. From time to time, major maintenance work may require team members to serve as primary or secondary on-call support over a weekend. Jobber is committed to maintaining a fair, transparent, and humane on-call experience. Your interview team will be happy to walk you through how we manage on-call responsibilities in practice
Skills
- 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)
- 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
- Strong understanding of AWS services relevant to the data domain, with hands-on experience leveraging them to design and implement data solutions
- Demonstrated success guiding teams through complex, high-impact projects while providing architectural direction and serving as a trusted technical lead
- Exceptional proficiency in software design, system architecture, and coding, with a focus on long-term maintainability, performance, and resilience
- Strong background in infrastructure-as-code (Terraform, CloudFormation), observability (logging, monitoring, tracing), and system reliability
- Exceptional communication skills, self-motivation, and resourcefulness, with the ability to navigate ambiguity, prioritize effectively, and deliver results in fast-paced environments
- Exposure to ML platforms and distributed compute frameworks (e.g., Ray, TensorFlow, PyTorch)
- Experience collaborating with Data Scientists to operationalize models, implement drift detection, or scale ML workloads
- Hands-on exposure to non–data engineering codebases, such as web application frameworks (Ruby on Rails) and modern front-end stacks (TypeScript/React)
- Familiarity with GraphQL, API layer design, and performance optimization
- Prior work on developer tooling or shared platforms that supported multiple engineering domains
- Knowledge of data privacy, security, and compliance in cloud-based data environments
- Knowledge of data privacy, security, and compliance considerations in a cloud-based data environment
Benefits
- Time off in lieu for incidents occurring outside of regular working hours during the on-call rotation
- Equity rewards
- Annual stipends for health and wellness
- Retirement savings matching
- An extended health package with fully paid premiums for body and mind
- A dedicated talent development program that includes career coaching and opportunities for career development
- Matching in RRSP, TFSA or FHSA
- Stock options
- Access to coaching, learning, and leadership programs to help you grow your career, reach your goals, and unlock your full potential
- Onboarding resources, tutorials, hackathons and buddies to support learning and provide opportunities to innovate
- Mentor/mentee opportunities
- Remote work
Company Overview
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