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 ThinkificAs 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 yetShip customer-facing analytics dashboards and features — this is production code, not just SQL and chartsWork directly with engineering teams to implement tracking services across our productsInterface with teams across the company who need data solutions, translating fuzzy requirements into concrete deliverablesRaise 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 teamWork with your team to conduct new technology research; bring fresh ideas and concepts to bear on how we integrate AI into our data workflowsThe 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 titleHas solid data engineering experience — you've built and maintained pipelines, worked with warehouses, and understand data modeling and qualityHas full-stack development experience — you've shipped production code that users interact with, not just internal toolingHas 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 upIs comfortable working across the stack and across disciplines; you don't need to be an expert everywhere, but you're not afraid to jump inFor 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 analyticsExperience with GCP and TerraformAny exposure to MLExperience white-labeling a BI tool or embedding analytics into a customer-facing productExperience building or maintaining event tracking systemsFamiliarity with modern data stack tools beyond dbt/BigQuery (Airflow, Dagster, etc.)Experience working in startup-style environments or autonomous teams within larger orgsExperience working in a SaaS environmentWe’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