Strategic Overview
Senior Data Engineer - Data Infra (Ontario, Canada) at Dandy is defined by the responsibilities and candidate requirements in the employer's listing.
The published role emphasizes work such as 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….
The role is listed for Canada with remote working arrangement, giving candidates the practical context needed to assess fit before applying. Relevant signals in the listing include Data Science & Analytics, Senior.
Key information at a glance
About This Role
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…
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,…
Key Responsibilities & Objectives
- 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
Required Qualifications & Candidate Blueprint
- 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
- 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
Salary & Benefits
Published compensation: CAD 133,600 – 167,000 / yearly
Full Job Description
The following is the complete job description supplied by the source. We sanitize unsafe markup and remove external links, but do not shorten or rewrite the employer's source content.
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
Track record of standing up new data engineering processes through ambiguity
Willingness to roll up your sleeves and fix problems hands-on, paired with intellectual curiosity and strong troubleshooting instincts
Bonus Points For
Exposure to healthcare or other regulated, compliance-heavy environments
Experience building infrastructure that supports ML/AI workflows or agentic, LLM-powered products
Experience building pipelines with compliance handling for PHI/PII data, particularly in healthcare
Req ID: J-1276
For full-time positions, Dandy offers a wide range of best-in-class, comprehensive, and inclusive benefits tailored to each country where we operate. Our local benefits packages typically include healthcare, dental, mental health support, parental planning resources, retirement savings options, and generous paid time off—ensuring our team members are supported no matter where they live and work.
Dandy is proud to be an equal-opportunity employer. We are committed to building a diverse and inclusive culture that celebrates authenticity to win as one. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, citizenship or immigration status, or any other legally protected characteristics.
Dandy also fully complies with the Americans with Disabilities Act (ADA). We are dedicated to embracing challenges and creating an accessible, inclusive workplace for all individuals. If you require any accommodations for your interview or have any questions beforehand, rest assured that we will do everything we can to meet your needs. Visit Dandy Careers for more!
Data Privacy Notice: By submitting your application, you consent to Dandy collecting, storing, and processing your personal information for recruitment purposes in accordance with our Privacy Policy and GDPR regulations. You have the right to access, rectify, or request the deletion of your data at any time by contacting Privacy Requests.
Editor’s Market Perspective (Our Custom Analysis)
Why This Position Matters
This opening may suit candidates whose experience matches Data Science & Analytics, Senior. Its strongest career signal is the scope of the work itself — particularly Design, build, and operate ingestion pipelines and connectors (e.g., Fivetran, dbt, BigQuery) that reliably land data from disparate source systems into our warehouse — rather than a generic title alone.
Resume & Application Strategy
For the application, mirror the employer's language where it truthfully matches your background: foreground Data Science & Analytics, Senior, quantify outcomes from comparable work, and place the most relevant experience near the top of the resume. If the listing specifies tools, platforms, leadership scope, or domain experience, use those exact terms in context instead of presenting an unrelated keyword list.
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