Data Engineer I

Docebo

. Build and fine-tune robust cloud data pipelines supporting analytics, data science, and product teams .

Posted 9/15/2026full-timeToronto • CanadaJuniorMid-Level💰 CA$68,600 - CA$91,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and maintaining cloud data pipelines, with strong skills in SQL and data transformation concepts. Proficient in using tools like dbt, Airflow, and cloud platforms such as Snowflake and BigQuery to support analytics and data science initiatives.

Highest-signal resume keywords

Cloud Data Pipeline DevelopmentSQL ProficiencyData Transformation ConceptsAirflow and Cloud ComposerData Quality Testing

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLData EngineeringData TransformationELT/ETLData Quality TestingPythonDbtAirflowBigQuerySnowflake

Tools & Technologies

DbtAirflowCloud ComposerSnowflakeBigQueryDatabricksGit

Industry Keywords

Data AnalyticsData ScienceData IngestionData TransformationCloud Platforms

Tech Stack

Tools & technologies

AirflowBigQueryCloudETLPythonSQL

About the role

Key responsibilities & impact

Build and fine-tune robust cloud data pipelines supporting analytics, data science, and product teams
Implement high-performance ELT/ETL transformations using tools such as dbt
Build, deploy, and maintain data ingestion and transformation jobs using Airflow and Cloud Composer
Write and execute data quality tests, including row counts, null checks, and reference validations
Investigate automated alerts, maintain system performance, and escalate deeper architectural changes when needed
Maintain schemas and naming conventions across Snowflake, BigQuery, or Databricks
Implement table and view enhancements
Document pipelines, schemas, and caveats
Collaborate with Analytics and Data Science teams to understand query needs and deliver optimized data structures

Requirements

What you’ll need

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, including joins, filters, and aggregations
Ability to query across cloud data platforms such as Snowflake, BigQuery, or Databricks
Strong foundational understanding of data transformation concepts
Comfort navigating dbt and Airflow under guided supervision
Familiarity with Python or similar languages
Familiarity with Git-based collaborative workflows
Ability to work from the office three days a week, Tuesday through Thursday
Legal authorization to work in Canada without current or future visa sponsorship

Benefits

Comp & perks

Employee Share Purchase Plan (ESPP) at a 15% discount
Competitive compensation package
Health benefits
Paid vacation days
Two company-wide Docebo Days
Floating holidays for cultural celebrations
Birthday off
Family coverage offering time off with children
Employee Resource Groups, including PRIDE, DWA, BIDOC, and Green Ambassadors
Company-wide events
Hybrid work flexibility with three office days and flexibility the rest of the week
Discretionary bonus incentive based on individual and company performance