Data Engineer

Data Engineer Thinkific is a learning commerce platform that helps learning businesses turn knowledge into impact. By bringing together community, courses, and content with commerce, we power transformative learning experiences that help businesses grow their revenue—and reach millions of learners around the world. We’re a team of 300+ Thinkers building products that matter. Every role at Thinkific contributes to raising the bar for online learning, supporting learning businesses, and creating real-world impact. You’ll work alongside curious, collaborative teammates who care deeply about what they build and who they build it for. We’re committed to a fair, inclusive, and human hiring experience. Our team is here to guide you every step of the way, so you always know what to expect! 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 n ... (truncated, view full listing at source)