Data Engineer - Up to $200k CAD + Bonus

Hunter Bond; Montreal; On-site; CAD 90,000 - 130,000; Full time

Job summary

Hunter Bond in Montreal, Canada seeks a Data Engineer / Database Developer to design, build, and optimize scalable cloud-based data systems in Azure. You will work across data engineering and ML workflows, developing Python-based data pipelines and supporting analytics initiatives.

The role emphasizes full data lifecycle ownership—from architecture and performance tuning to enabling advanced analytics and ML use cases in a fast-growing tech environment.

Qualifications

• 5 years of experience in data engineering or database development.
• Strong Python experience and SQL relational design know-how.
• Hands-on with Microsoft Azure data services (Azure SQL, Data Factory, Synapse).

Responsibilities

• Design and build SQL databases from scratch, ensuring scalability, reliability, and performance.
• Optimize 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 ML 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 with cross-functional teams to understand data requirements and deliver solutions.

Skills

SQL

Python

Azure Data Factory

Data modelling

ETL

Azure Synapse

Tools

Azure SQL

Azure Data Factory

Azure Synapse

Job description

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
• 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