Postuler

Publié il y a 15 jours

Data Engineer - Up to $200k CAD + Bonus

@ Hunter Bond

Montréal, Québec

Temps plein
Postuler
SIGNAUX

Responsabilités :

  • Design and build SQL databases from scratch, ensuring scalability, reliability, and performance
  • Optimise and maintain existing database systems, improving query performance and efficiency
  • Architect, implement, and manage cloud-based databases and data solutions in Azure
  • Develop and maintain data pipelines to support analytics and machine learning workloads
  • Collaborate with data scientists to prepare and structure data for ML modelling
  • Contribute to Python-based machine learning models and data processing workflows

Résumé des exigences :

  • Work closely with cross-functional teams to understand data requirements and deliver solutions
  • Skills & Experience:
  • 5 years of experience in data engineering or database development roles
  • Strong experience working with Python
  • Experience building and managing databases from the ground up
  • Hands-on experience with Microsoft Azure data services (e.g.
Source et dates

Type de source non vérifié · apify-linkedin

Date publiée par l’employeur
2026-10-26
Première détection par notre source
2026-11-11
Mise à jour du dossier source
2026-11-11

Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.

Hunter Bond

ChampValeur
Offres sur Jobsy11
Description

Title: Senior Data Engineer

Client: Fintech

Salary: Up to $200k CAD + Bonus

Location: Montreal/Hybrid

About the Client:

We are partnering with an innovative, fast-growing technology company operating at the forefront of data, cloud, and machine learning. The team builds scalable, data-driven platforms that support advanced analytics and AI-powered applications across industries including fintech, healthcare, and digital services.

Their mission is to turn complex data into actionable intelligence through robust engineering, modern cloud infrastructure, and cutting-edge machine learning techniques. This is a fantastic opportunity for a data-focused engineer who enjoys building systems from the ground up and working across both data engineering and ML workflows in a high-impact environment.

The Role:

We are looking for a Data Engineer / Database Developer (2–5 years’ experience) to join a growing data team. You will be responsible for designing, building, and optimising scalable database systems, primarily within a cloud-based Azure environment, while also contributing to machine learning modelling and data pipeline development in Python.

This role is ideal for someone who enjoys owning the full data lifecycle — from database architecture and performance tuning to enabling advanced analytics and ML use cases. You’ll collaborate closely with engineers, data scientists, and stakeholders to deliver high-quality, efficient, and scalable data solutions.

Key Responsibilities:

  • Design and build SQL databases from scratch, ensuring scalability, reliability, and performance
  • Optimise and maintain existing database systems, improving query performance and efficiency
  • Architect, implement, and manage cloud-based databases and data solutions in Azure
  • Develop and maintain data pipelines to support analytics and machine learning workloads
  • Collaborate with data scientists to prepare and structure data for ML modelling
  • Contribute to Python-based machine learning models and data processing workflows
  • Ensure best practices in data governance, security, and integrity
  • Work closely with cross-functional teams to understand data requirements and deliver solutions

Skills & Experience:

  • 5 years of experience in data engineering or database development roles
  • Strong experience working with Python
  • Strong expertise in SQL and relational database design (e.g. schema design, indexing, optimisation)
  • Experience building and managing databases from the ground up
  • Hands-on experience with Microsoft Azure data services (e.g. Azure SQL, Data Factory, Synapse or similar)
  • Solid understanding of data modelling, ETL processes, and data architecture principles
  • Experience with performance tuning and query optimisation
  • Strong problem-solving skills and attention to detail

Nice to Have (Not Required):

  • Experience with big data tools or distributed data systems
  • Familiarity with ML frameworks (e.g. scikit-learn, TensorFlow, PyTorch)
  • Knowledge of data warehousing concepts and modern data stack tools
  • Exposure to DevOps practices, CI/CD, or infrastructure-as-code
  • Experience working in fast-paced or startup environments

Benefits:

  • Comprehensive Health & Wellness Package, including mental health support
  • Tech Upgrade Stipend for your home setup
  • Learning & Development Budget for courses, certifications, and conferences
  • Quarterly Innovation Days to explore new ideas and technologies
  • Adventure Days — one paid day per quarter to do something you love
  • Gym access, wellness initiatives, and encouraged mental health days
  • Flexible working options and a collaborative, growth-focused environment

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