Manager, Data Engineering

About this role

DO YOU GET EXCITED TO WORK WITH DATA & LEAD IMPACTFUL TEAMS?

Then Jobber might be the place for you! We’re looking for a Manager, Data Engineering to be part of our Data org.

Jobber exists to help people in small businesses be successful. We work with small home service businesses, like your local plumbers, painters, and landscapers, to transform the way service is delivered through technology. With Jobber they can quote, schedule, invoice, and collect payments from their customers, while providing an easy and professional customer experience. Running a small business today isn’t like it used to be—the way we consume and deliver service is changing rapidly, technology is evolving, and customers expect more. That’s why we put the power and flexibility in their hands to run their businesses how, where, and when they want!

Our culture of transparency, inclusivity, collaboration, and innovation has been recognized by Great Place to Work, Canada’s Most Admired Corporate Cultures, and more. Jobber has also been named on the Globe and Mail’s Canada’s Top Growing Companies list, and Deloitte Canada’s Technology Fast 50™, Enterprise Fast 15, and Technology Fast 500™ lists. With an Executive team that has over thirty years of industry experience of leading the way, we’ve come a long way from our first customer in 2011—but we’ve just scratched the surface of what we want to accomplish for our customers.

We help employees grow professionally; we have a ton of onboarding resources, tutorials, hackathons and buddies to support learnings and provide opportunities to innovate. We have a range of experience levels on teams which allows for mentor/mentee opportunities. Leaders at Jobber work with empathy and support employees to build healthy work-life harmony. Bring your dedication and passion to this job to fulfill your goals.

The Team:

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; and data integrity and governance.

The role:

Reporting to the Director of Data, the Manager, Data Engineering will lead a team of data engineers. You will also partner with the team’s Technical Program Manager to prioritize initiatives and collaborate on building quarterly roadmaps. This role’s scope is large as it spans both Data and ML platforms.

A key aspect of this role is managing the team’s performance, supporting individual growth, ensuring high-quality deliverables, and scaling the team as needed. You will also play a key role in shaping technical decisions, collaborating with technical leads, principals, and distinguished engineers.

The Manager, Data Engineering will:

- Invest in their people — leading and growing a team of up to 8 engineers, coaching and stretching each team member to do the best work of their careers while driving real impact across Jobber.

- Continuously sharpen how the team delivers, building processes and self-serve capabilities that compound velocity and scale impact well beyond the team.

- Own the vision, strategy, and roadmap for data infrastructure that sets the standard — high-performance, elegantly scalable, and cost-efficient data stores, compute engines, and orchestration systems built to power Jobber for years to come.

- Lead from the front and stay close to the craft — shaping systems design, pressure-testing architectural decisions, conducting meaningful code reviews, and diving deep into the code alongside your team whenever the moment calls for it.

- Champion resilient, real-time data systems that teams can trust — observable, governed, and built to recover gracefully, with proactive monitoring and best-in-class security, integrity, and compliance woven in from the start.

- Forge strong partnerships across engineering, analytics, and go-to-market teams to deliver data in a timely accurate manner and craft the tools, automation, and solutions that accelerate workflows and unlock real outcomes for Jobber's small business customers.

- Push the boundaries of what's possible with AI — embedding it into the data strategy and empowering your team to continuously explore, experiment, and elevate the state of the art in data tooling.

To be successful, you should have:

- 2+ years managing engineering teams with a proven track record of shipping high-quality software/data solutions.

- 4+ years in software or data engineering, backed by a deep technical foundation across distributed data systems, orchestration frameworks, cloud infrastructure, performance tuning and scaling strategies.

- Experience building highly available systems that adhere to strict SLOs, building automations to proactively resolve issues and setting up workflows to recover critical systems quickly.

- The ability to lead and adapt in a fast-moving, agile environment cultivating a culture of continuous learning, critical thinking, and creative problem-solving.

- Exceptional collaboration and communication skills, with a talent for partnering across engineering, product, analytics, and data science to turn ambitious ideas into shipped outcomes.

- A strategic mindset and strong roadmap-planning instincts, with a history of shaping infrastructure initiatives that deliver measurable, lasting impact.

Highly desired, but not a dealbreaker:

- Hands-on experience with Snowflake, dbt, Airflow and Kafka.

- Understanding of lambda and/or kappa architecture.

- Background in building self-service data tooling and workflow automation for data teams.

- Experience in working with Product Engineering teams to influence upstream data design and instrumentation.

- Exposure to data science and machine…