Data Engineer I: Build Scalable Cloud Pipelines

Socket.dev; Toronto; Hybrid; CAD 70,000 - 95,000; Full time

Benefits offered by this job

Health benefits

Vacation days

Employee Stock Purchase Plan

Hybrid work model

Job summary

Docebo in Toronto is seeking a Data Engineer I to build and tune robust cloud data pipelines powering analytics, data science, and product teams. You will tackle real-world architecture challenges and collaborate with world-class engineers to shape how learning experiences reach millions of users.

The role demands strong data modeling, data quality focus, and hands-on work with ELT/ETL, dbt, Airflow, Python, and Git. Join a team that values trust, transparency, and growth.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical field (or equivalent practical experience).
• 2-3 years of hands-on experience in data engineering, BI engineering, or equivalent project-driven environments.
• Exceptional ability to write clean SQL (joins, filters, aggregations) and query across cloud data platforms like Snowflake, BigQuery, or Databricks.
• Strong foundational understanding of data transformation concepts and comfort navigating tools like dbt and Airflow under guided supervision.
• Familiarity with Python (or similar languages) and Git-based collaborative workflows to ship clean code efficiently.

Responsibilities

• 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.

Skills

SQL mastery

Data modeling

Data quality focus

Analytical mindset

Team collaboration

Education

Bachelor's degree in Computer Science, Engineering, Mathematics, or related field

Tools

dbt

Airflow

Python

Git

Snowflake

BigQuery

Databricks

Job description

Docebo in Toronto is seeking a Data Engineer I to build and tune robust cloud data pipelines powering analytics, data science, and product teams. You will tackle real-world architecture challenges and collaborate with world-class engineers to shape how learning experiences reach millions of users.

The role demands strong data modeling, data quality focus, and hands-on work with ELT/ETL, dbt, Airflow, Python, and Git. Join a team that values trust, transparency, and growth.