Data Engineer I

Artificial Intelligence. Actual Impact.

At Docebo, we’re using AI to change how people learn at work—and we mean actually change it. We’re an AI-powered learning platform that helps organizations create, deliver, and manage training all in one place. But our real mission goes deeper: we help teams move faster, work smarter, and focus on the work that truly matters. Our platform is built with intelligent, time-saving tools that personalize learning, eliminate busywork, and turn training from a checkbox into a superpower. The result? Better experiences for learners and real results for businesses.

We’re shaping the future of learning with a team that isn’t afraid to challenge the status quo. If you're excited by the idea of using AI to make work-life better for real people–you’ll feel right at home here. And it’s not just what we build, it’s how we show up. At Docebo, our values aren’t just posters on the wall—they guide how we work every day. We call it the Docebo Heart : trust by default, assume positive intent, and create space for different perspectives to thrive.

So… what are you waiting for? Join 900+ Docebians around the world and help us reinvent the way people learn, because learning never stops.

🚀 The Adventure Ahead

As our Data Engineer I, you will build and fine-tune the robust cloud data pipelines that power our analytics, data science, and product teams. You’ll tackle real-world architecture challenges, collaborate with world-class engineers, and directly shape how intelligent learning experiences reach millions of users worldwide.

We are seeking engineers who bring deep analytical rigor to data modeling and relentless dedication to data quality.

🛠️ The Day-to-Day

Engineer the Flow: Implement high-performance ELT/ETL transformations using tools like dbt based on innovative specs from senior engineers and architects.

Orchestrate Data Jobs: Build, deploy, and maintain seamless data ingestion and transformation jobs powered by Airflow and Cloud Composer.

Guard Data Quality: Write and execute vital data tests—including row counts, null checks, and reference validations—to keep our datasets clean and trusted.

Monitor & Resolve: Proactively investigate automated alerts, ensuring peak system performance and escalating deeper architectural changes when needed.

Shape Lakehouse Architecture: Maintain pristine schemas and naming conventions across Snowflake, BigQuery, or Databricks while implementing table and view enhancements.

Document & Empower: Create clear documentation for pipelines, schemas, and caveats so the entire engineering team can safely build on your foundation.

Partner & Collaborate: Work closely alongside Analytics and Data Science teams to deeply understand their query needs and deliver optimized data structures.

⚡ Your Superpowers

Solid Academic & Technical Foundation: Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related technical field (or equivalent practical experience).

Early Career Momentum: 2-3 years of hands-on experience in data engineering, BI engineering, or equivalent project-driven environments.

SQL Mastery: Exceptional ability to write clean SQL (joins, filters, aggregations) and query across cloud data platforms like Snowflake, BigQuery, or Databricks.

ETL/ELT Aptitude: Strong foundational understanding of data transformation concepts and comfort navigating tools like dbt and Airflow under guided supervision.

Code & Version Control Literacy: Familiarity with Python (or similar languages) and Git-based collaborative workflows to ship clean code efficiently.

Our Hybrid Work Philosophy 🤝

Great work can happen anywhere but coming together helps us go further. Our team spends three days a week in the office (Tuesday-Thursday) to collaborate, solve problems, and learn from each other. With flexibility the rest of the week, it’s a balance designed to help everyone do their best work and keep growing.

Our Total Rewards Philosophy 🎉