Senior Data Engineer - Data Infra (Ontario, Canada)
About this role
Dandy is focused on modernizing the dental industry, a sector valued at over $400B, by deploying technology to simplify and update operational functions. The company is building the core operating system for dental offices globally, aiming to empower clinicians and their teams with necessary tools and support. This role sits within the Data Infrastructure team, which is responsible for the entire data platform—including data ingestion, pipeline construction, and the warehouse that feeds critical downstream applications used by Sales, Marketing, Finance, and ML teams. This is an opportunity for a Senior Data Engineer to have a significant, foundational impact on how the entire company leverages its data.
The core of this position involves transforming raw data into reliable, self-serve data products, setting the groundwork for an AI/agent-ready data platform. The engineer will design and maintain the data infrastructure that supports decision-making across multiple departments. This role is ideal for someone who thrives on building scalable systems from the ground up and enjoys bridging the gap between complex data engineering and direct business needs.
Candidates who excel in this role possess strong analytical instincts and a proactive approach to solving problems within an ambiguous, high-growth startup setting. A self-starter who is curious about integrating advanced concepts like LLMs into data workflows would be a strong fit for this position.
What you will do
- Design, build, and operate ingestion pipelines and connectors, utilizing tools like Fivetran and dbt, to reliably move data from various source systems into the data warehouse.
- Own and evolve core platform components, including dbt models, the semantic layer, data quality monitoring, and orchestration processes.
- Collaborate with stakeholders across Finance, Go-to-Market, Manufacturing, and ML teams to translate specific business requirements into governed, self-serve data products.
- Develop the platform to support AI and agent-based workflows by implementing governed data access and semantic layers accessible by LLMs/agents.
- Establish and maintain the necessary guardrails to ensure the safety and governance of these AI-powered data access mechanisms at scale.
What you need
- Possess at least five years of experience in a data engineering, data platform, or SQL-heavy analytics engineering role, with experience in high-growth startup environments being preferred.
- Demonstrated track record of successfully building and maintaining data ingestion pipelines, connectors, and transformation workflows using tools such as dbt in a production setting.
- Expert-level proficiency in SQL is required, complemented by working fluency in Python or a similar language for platform tooling and automation.
- Hands-on experience with BI/analytics tooling such as Looker and Hex, along with a perspective on how to integrate these tools into a larger data platform.
- Proven ability to work cross-functionally to gather requirements and establish consensus on crucial data platform decisions.
- Experience in standing up new data engineering processes when working within ambiguous environments.
- A willingness to troubleshoot issues hands-on, coupled with strong intellectual curiosity and troubleshooting instincts.
Nice to have
- 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
Benefits
- Healthcare
- Dental
- Mental health support
- Parental planning resources
- Retirement savings options
- Generous paid time off
Skills and tech stack
Questions candidates ask
What is the remote policy?
The role is listed as Canada - Remote. Dandy offers a wide range of best-in-class, comprehensive, and inclusive benefits tailored to each country where they operate.
What is the compensation structure?
The compensation offered ranges from CA$133.6K to CA$167K, and the package also includes equity and a bonus.
What is the primary tech stack for data transformation?
The role involves building pipelines using tools like Fivetran and dbt, with data landing in BigQuery.
What is the team structure like?
The Data Infrastructure team owns the entire data platform, which supports numerous downstream teams including Sales, Marketing, Manufacturing, People, Finance, and ML.