Data Engineer

iA Financial GroupMontreal, QC
Hybrid

About The Position

As a Data Engineer, you will play a key role in the design, industrialization, and optimization of data pipelines and artificial intelligence solutions. You will work closely with multidisciplinary teams to deliver high-value, impactful solutions to the organization. As a Data Engineer, you will be at the heart of our mission.

Requirements

  • A minimum of 7 years of relevant experience in data engineering, ETL development, or related fields.
  • Holds a university degree in computer science or a related discipline.
  • Demonstrates strong expertise in designing and orchestrating ETL/ELT pipelines using tools such as Azure Data Factory, with excellent SQL skills, knowledge of SSIS, and a solid understanding of data modeling (Data Vault, star schema, etc.).
  • Has strong experience with cloud databases, particularly Snowflake, and managing Azure platforms.
  • Acts as a technical leader with solid experience in Databricks (model management modules, Mosaic AI, Unity Catalog).
  • Is familiar with DevOps and MLOps practices, including CI/CD pipelines, solution and model monitoring, and thrives in agile, multidisciplinary environments (Scrum/Lean).
  • Possesses excellent communication skills (both written and verbal), strong initiative, rigor, and a constant focus on quality.
  • Is fluent in French and has an intermediate level of English.

Nice To Haves

  • Experience in the insurance or financial services industry is considered an asset.

Responsibilities

  • Designing, developing, and maintaining high-performance, secure, and scalable data pipelines (ETL/ELT).
  • Contributing to the implementation and evolution of data management solutions (data warehouses, data marts, data lakes).
  • Preparing, transforming, and structuring data required for training supervised machine learning models.
  • Developing, testing, deploying, and industrializing machine learning and AI models in cloud environments (Azure, Snowflake, Databricks).
  • Implementing and maintaining DevOps and MLOps practices, including continuous integration, pipeline monitoring, and model reproducibility.
  • Collaborating with Product Owners, Product Managers, data scientists, architects, and business stakeholders to translate business needs into concrete technical solutions.
  • Documenting delivered solutions and contributing to their sustainability and continuous improvement.

Benefits

  • Flexible group insurance
  • Competitive pension plan
  • Stock purchase plan
  • Vacation and wellness/personal development days
  • Telemedicine
  • Employee and family assistance program
  • Ergonomic furniture program
  • Performance bonus
  • Discounts on iA products
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