Dandy is transforming the massive and antiquated dental industry—an industry worth over $400B. Backed by some of the world’s leading venture capital firms, we’re on an ambitious mission to simplify and modernize every function of the dental practice through technology. As we expand our reach globally, Dandy is building the operating system for dental offices around the world—empowering clinicians and their teams with technology, innovation, and world-class support to achieve more for their practices, their people, and their patients.

About the Role

Dandy is hiring a hands-on Senior Data Engineer to join our rapidly growing venture-backed company. The Data Infrastructure team owns the data platform — ingestion, pipelines, and the warehouse feeding downstream tools like Looker and Hex — that Sales, Marketing, Manufacturing, People, Finance, and ML teams rely on every day. In this role, you'll build and scale the infrastructure that turns raw data into trusted, self-serve data products, and help lay the foundation for an AI/agent-ready data platform. It's a rare chance to have outsized, ground-floor impact on how the entire company works with data. This role will be remote based in Ontario, Canada.

What You'll Do

• Design, build, and operate ingestion pipelines and connectors (e.g., Fivetran, dbt, BigQuery) that reliably land data from disparate source systems into our warehouse
• Own and evolve core platform components — dbt models and the semantic layer, data quality/observability, and orchestration — that power our BI tools and internal analytics apps
• Partner directly with stakeholders across Finance, GTM, Manufacturing, and ML to translate business needs into governed, self-serve data products
• Help extend the platform to support AI and agent-based workflows — governed data access, semantic layers usable by LLMs/agents, and the guardrails to keep that safe at scale
  

What We're Looking For

• 5+ years of experience in a data engineering, data platform, or SQL-heavy analytics engineering role (high-growth startup environments highly preferred)
• Track record of building data ingestion pipelines, connectors, and transformation workflows (dbt or equivalent) in production
• Expert-level SQL, plus working fluency in Python or a similar language for platform tooling and automation
• Hands-on exposure to Looker, Hex, dbt, and/or equivalent BI/analytics tooling, with a point of view on evaluating and integrating them into a broader platform
• Demonstrated ability to work across teams to gather requirements and drive consensus on data platform decisions