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Data Engineer, Investments

  • Quebec, QC, Canada

Full-time

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Job details

Job type
Full-time
Experience
Has 5 to 10 years of experience in data engineering, ETL/ELT development, or a related field.
Posting language
English
Posted

Original job description

Description

Job Title

Data Engineer

Internal Title: Data Analyst

Build the future with us

As a Data Engineer, you will play a key role in the design, industrialization, and optimization of modern data pipelines on the Google Cloud platform. You will actively contribute to building a robust, scalable, and AI-driven data architecture.

You will work closely with multidisciplinary teams to deliver concrete, high value-added solutions for the organization.

This position represents a great opportunity to showcase your skills and fully leverage your potential within a caring and reliable company. Here, people and their development are at the heart of our priorities, fostering an environment conducive to collaboration and innovation.

What You Will Accomplish With Us

As a Data Engineer, you will be at the core of our mission. Here are your main responsibilities:

Data Engineering & GCP Platform

  • Design, develop, and maintain high-performance, secure, and scalable data pipelines (ETL/ELT) on Google Cloud Platform (GCP).
  • Leverage GCP services such as: BigQuery (analytics data warehouse) Cloud Storage (raw data and data zones storage) Dataproc (distributed Spark/Hadoop processing) Cloud Run (deployment of data services and microservices) Cloud Workstations (development environments)
  • Participate in the implementation of modern data lakehouse architectures.

Orchestration and Automation

  • Design and orchestrate data processing pipelines using Prefect.
  • Implement robust, observable, and resilient workflows.

Code Development and Governance

  • Develop in modern environments (VS Code / Cloud Workstations).
  • Manage source code using GitHub.
  • Implement CI/CD pipelines with GitHub Actions.
  • Automate deployments and infrastructure using Terraform (Infrastructure as Code).

Data & AI Enablement

  • Prepare, transform, and structure data to support analytics and artificial intelligence use cases.
  • Collaborate with data scientists to facilitate access to reliable and governed data.

DevOps, DataOps and Reliability

  • Implement DevOps/DataOps practices: Automated testing Pipeline monitoring Error handling and alerting
  • Ensure data quality, traceability, and governance.

Collaboration & Delivery

  • Work collaboratively with: Product Owners and Product Managers (PO & PM) Architects, Data Scientists, Business partners
  • Translate business needs into robust technical solutions.
  • Document solutions and contribute to their continuous evolution.
  • Participate in an on-call rotation one week per month, with additional compensation.

What Could Accelerate Your Success In This Role

We are looking for someone who:

  • Has 5 to 10 years of experience in data engineering, ETL/ELT development, or a related field.
  • Holds a degree in computer science, software engineering, or an equivalent field.
  • Masters data modeling concepts (Data Vault, star schema, etc.).
  • Has strong experience with: BigQuery and cloud analytics environments Distributed processing (Spark / Dataproc)
  • Has expertise in pipeline orchestration (e.g., Prefect, Airflow, or equivalent).
  • Is comfortable with modern development practices: GitHub, GitHub Actions CI/CD Infrastructure as Code (Terraform)
  • Is familiar with microservices-oriented architectures (Cloud Run or equivalent).
  • Understands data governance, security, and cloud access management (IAM).
  • Demonstrates strong analytical skills and the ability to propose relevant solutions.
  • Shows autonomy, rigor, and a constant focus on quality.
  • Thrives in an agile and multidisciplinary environment.
  • Has excellent proficiency in French, both spoken and written.
  • Has an intermediate level of English, as the role involves leading presentations and meetings with internal and external stakeholders on a weekly basis.

Important Assets

  • Experience in a production GCP environment
  • Knowledge of MLOps/DataOps practices
  • Knowledge of investment and financial data (portfolios, transactions, market prices), a major asset
  • GCP certification (e.g., Professional Data Engineer)

Why you’ll enjoy working with us

  • An environment focused on innovation and modern data (GCP-first)
  • A strong culture of collaboration between IT, data, and business teams
  • A setting that encourages continuous learning and experimentation
  • A flexible hybrid work environment
  • Competitive benefits: flexible group insurance, competitive retirement plan, employee share purchase plan, vacation and wellness/personal development days, telemedicine, employee and family assistance program, ergonomic equipment program, performance bonus, discounts on iA products, and more!

Apply now and take charge of your career, where your talent truly matters!

Hesitating to apply?

At iA, we believe in potential and value diverse experiences. If this role inspires you, go ahead and apply, your place might be with us, and we want to get to know you!
More about this job

Responsibilities

You will design, develop, and maintain high-performance data pipelines on Google Cloud Platform while ensuring data quality and governance. You will also collaborate with multidisciplinary teams to translate business needs into scalable, AI-driven data solutions.

Requirements

The role requires 5 to 10 years of experience in data engineering and a degree in computer science or software engineering. Candidates must possess strong expertise in GCP, data modeling, pipeline orchestration, and modern development practices like CI/CD and Infrastructure as Code.

Skills

  • Data engineering
  • Google Cloud Platform
  • BigQuery
  • ETL/ELT
  • Spark
  • Dataproc
  • Prefect
  • Terraform
  • GitHub Actions
  • CI/CD
  • Data modeling
  • Data governance
  • Cloud Run
  • DataOps
  • DevOps
  • Microservices

Benefits

  • Flexible group insurance
  • Competitive retirement plan
  • Employee share purchase plan
  • Vacation days
  • Wellness and personal development days
  • Telemedicine
  • Employee and family assistance program
  • Ergonomic equipment program
  • Performance bonus
  • Discounts on iA products

Visa sponsorship

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Categories

  • Data & Analytics
  • Technology
  • Software
  • Finance & Accounting
  • Engineering

Keywords

  • Data Engineering
  • GCP
  • BigQuery
  • Cloud Storage
  • Dataproc
  • Cloud Run
  • ETL
  • ELT
  • Prefect
  • GitHub
  • GitHub Actions
  • CI/CD
  • Terraform
  • Infrastructure as Code
  • Data Lakehouse
  • Data Modeling
  • Data Vault
  • Star Schema
  • DataOps
  • DevOps
  • IAM
  • MLOps
  • Financial Data
  • Agile
  • Microservices

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