Jobs / Canada / Databricks

Manager, Engineering - AI/BI

Databricks · 🇨🇦 Vancouver, Canada

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  • No government sponsor record hereNo government sponsor record covers this employer in this country.
  • The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
  • No salary bar for this routeCanada has no single salary bar: the employer usually needs a positive LMIA. Pay at or above the provincial median wage + 20% (e.g. C$36.92/h in Ontario) puts it in the high-wage stream. Source: https://www.canada.ca/en/employment-social-development/services/foreign-workers/median-wage.html, rules effective 2026-07-17.
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Sponsor Radar — Databricks

Sponsorship not verified for this country

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About the role

RDQ226R533 At Databricks, we are passionate about helping data teams solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. We are the “AI/BI” team responsible for making Databricks the best product for business users to create, find and consume data insights. We work on 4 key pillars Dashboards, Genie, Databricks One and Unity Catalog Business semantics. UC Business semantics allow users to define business metrics and agent metadata in centrally governed systems for trusted access. Databricks One offers users a simplified experience tailored for non technical users to find and consume data insights. Genie lets users talk to their data with state of the art text-to-SQL and Dashboards lets users run their day to day business. We're seeking a dedicated Engineering Leader who will help grow the Data visualization and UC Business Semantics teams.These teams will be tackling a number of challenging fullstack problem spaces, including: making visualizations easy to consume, enabling dashboards to be highly interactive, creating compelling augmented analytics experiences, providing best in class low/no code authoring, and increasing the analytical expressivity of our business semantics products. You will report directly to the Senior Manager of Engineering. The main responsibilities include: • You will lead a talented engineering team of full stack engineers and SMEs focused on one of the above initiatives. • You will oversee sustained recruitment of top-tier talent, and developing talent on the team. • You will build processes to implement product vision and strategy, according to organizational goals and priorities. • You will build software that is not just high quality, but easy to operate. • You will manage technical debt, including long-term technical architecture decisions, and balance product roadmap. What we look for: • Great at hiring and developing talent • Great at creating efficient processes that increase velocity and quality • 2+ years of experience in managing teams that build and operate systems in a SaaS environment • 5+ years of experience with distributed systems and building platforms and services and best in class application experience which serve multiple product teams and customers • Have experience in scaling engineering teams from 5 to 20+ • Team player that will work with other departments (PM, CS) and engineering teams. • BS or higher in Computer Science, or a related field • Strong track record of attracting, hiring, and retaining top engineering talent • Experience managing distributed teams across multiple locations. • Adaptability and resilience in a fast-paced, rapidly evolving tech environment Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticpates utilizing the full width of the range. The to

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Source: Greenhouse (employer board) First seen: 2026-08-18 Last confirmed: 2026-10-03 How our data works → Report this job

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