Data Engineer at Thinkific in Distributed - Canada, Ontario, CA

Are you a data engineer who loves writing code, or a full-stack developer with a knack for data? Either way, we'd love to talk. We're looking for an Intermediate Data Engineer to join us at Thinkific

As an Intermediate Data Engineer on our Data team, you'll be closely collaborating with engineering teams, designers, and stakeholders across the company to solve data problems that span the full stack — from pipelines and infrastructure to customer-facing data products. You'll be part of a small, dynamic team — the problems you'll work on won't always come with a neat brief, and we need someone who takes ownership and runs with it. Reporting to a Principal Data Engineer, your work will directly impact both internal decision-making and customer success.

Your goal will be to help shape our data products and infrastructure to have a top-line impact on our company goals. Here's how you'll accomplish this:

• Take ownership of undefined problems — dig in, scope the work, and ship solutions, whether that's a pipeline, a dashboard, a tracking implementation, or something we haven't thought of yet
• Ship customer-facing analytics dashboards and features — this is production code, not just SQL and charts
• Work directly with engineering teams to implement tracking services across our products
• Interface with teams across the company who need data solutions, translating fuzzy requirements into concrete deliverables
• Raise the bar on technical quality across the data team — through architecture decisions, reducing tech debt, code reviews, and bringing software development best practices to a high-performing data team
• Work with your team to conduct new technology research; bring fresh ideas and concepts to bear on how we integrate AI into our data workflows

The person we have in mind likely:

• Has 3–5 years of experience working across data engineering, full-stack development, analytics, or some combination — we care more about range than a specific title
• Has solid data engineering experience — you've built and maintained pipelines, worked with warehouses, and understand data modeling and quality
• Has full-stack development experience — you've shipped production code that users interact with, not just internal tooling
• Has hands-on experience with dbt and BigQuery or similar stacks (Snowflake, Databricks, etc.)
• Is self-motivated and resourceful — you ship things, communicate clearly across technical and non-technical teams, and are always looking to level up
• Is comfortable working across the stack and across disciplines; you don't need to be an expert everywhere, but you're not afraid to jump in
• For reference, our current stack is primarily dbt (SQL) with Python for data work, Looker for our Analytics layer, and React, TypeScript (with some Ruby), and embedded Looker on the product side — but we're more interested in your engineering fundamentals than specific language experience.
• Loves to learn and grow, They’ve found (and keep looking for) ways to level up their skills in this field, whether that’s through formal education, gaining professional experience, or maybe even building their own business 

These things would also be nice, but we think you could learn them on the job:

• Experience with LLM/agent development — building AI-powered data products, automated workflows, or integrating LLMs into data pipelines and analytics
• Experience with GCP and Terraform
• Any exposure to ML
• Experience white-labeling a BI tool or embedding analytics into a customer-facing product
• Experience building or maintaining event tracking systems
• Familiarity with modern data stack tools beyond dbt/BigQuery (Airflow, Dagster, etc.)
• Experience working in startup-style environments or autonomous teams within larger orgs
• Experience working in a SaaS environment

We’re committed to fair and transparent pay that reflects both where you are and where you can grow to. This role has a salary range base of $88,200 - $110,200 - $132,200 designed to capture the full journey from developing skills to excelling in the position. Most new hires start between the minimum and midpoint, which aligns with being fully capable in the role. Salaries above the midpoint are typically reserved for team members who have demonstrated strong, consistent performance, deep expertise, and a significant positive impact within the role.

For high-demand or hard-to-fill positions like this one, we may hire above midpoint for candidates who bring exceptional experience, skills, or impact potential.

Diversity, Equity, Inclusion and Belonging & Accessibility

This is just our initial idea of who we’re looking for! At Thinkific, we know that people have unique career journeys. If your experience is close to what we’ve described but you feel that you might be missing a few of the requirements, please still apply! We believe in equal opportunity and are committed to diversity, equity, inclusion, and belonging across every facet of our business.

We’re also committed to providing a comfortable and accessible interview experience for every candidate. If there are any accommodations our team can make throughout our hiring process (big or small), please let us know.