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Vooban

Custom AI solutions for digital transformation

Lead Data Engineer

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeNo salary listedHybrid

About the Job

Requirements

  • Mastery of Python (PySpark) and SQL for manipulating and transforming data.
  • Six to eight years of development experience, including some experience providing technical guidance to a team or project.
  • Experience making architecture decisions and supporting a team in executing them.
  • Comfort with Git/GitLab, CI/CD, and structured versioning and deployment practices.
  • Significant experience with Databricks and AWS.
  • Understanding of testing and validation, including unit tests, quality assurance, and reviews, and ability to promote their adoption.
  • Ability to communicate technical topics clearly and align people toward a shared goal.
  • Ability to work autonomously, analytically, and resourcefully, and maintain direction in complex situations.

Responsibilities

  • Define and evolve technical solution architecture, emphasizing robustness and scalability.
  • Coach and develop a data engineering team through code reviews, pair programming, and feedback.
  • Translate business needs into concrete, prioritized technical decisions.
  • Serve as a technical reference for AI, operations research, and business intelligence teams and project stakeholders.
  • Contribute hands-on to critical code and set an example for the team.
  • Ensure quality, testing, and validation to support reliable deliveries.
  • Lead production releases and promote versioning, merge-request, and CI/CD practices through Git/GitLab.
  • Integrate AI tools into personal and team workflows to increase impact and efficiency.

Desired Qualifications

  • Knowledge of Snowflake, Google Cloud Platform, or Microsoft Fabric may be useful for some projects but is not required.

About the Company

Vooban

Custom AI solutions for digital transformation

Vooban provides end-to-end, project-based AI-enabled digital transformation services for medium to large enterprises, integrating AI, data engineering, and software development. It does not build its own AI models; instead it selects commercially available models and customizes them for clients. The company differentiates itself through turnkey project delivery, practical integration of off-the-shelf AI models, cross-industry expertise, and a strong focus on ROI supported by partnerships and acquisitions. Its goal is to accelerate clients' digital transformation and raise operational efficiency across industries in North America.

Company size
201-500
Company stage
Not listed
Total funding
Not listed
Headquarters
Quebec City, Canada
Founded
2011

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