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Data Solutions Developer Jobs in Montreal, QC (NOW HIRING)

Data Modelers: You believe a great answer starts with a well-designed model, and you take pride in structuring data so others can trust it. Applied AI Builders: You're fluent in prompt and context ...

New

Apply DevOps practices to improve the development and deployment of data solutions. * Identify opportunities to automate manual work and improve data delivery processes. * Follow data governance ...

New

... Engineering, Analytics, and Data Platform solutions. This senior role influences long-term technology direction, ensures architectural coherence across the organization, and drives adoption of ...

Collaborate with software engineers to integrate data solutions into customer-facing products and internal systems. What We're Looking For * 5-8 years of experience in Data Engineering, Analytics ...

... data solutions that meet the needs of development, production, analytics, and AI teams. Working ... Minimum of 8 years of experience in software development or data engineering. * Significant ...

Collaborate with software engineers to integrate data solutions into customer-facing products and internal systems. What We're Looking For * 5-8 years of experience in Data Engineering, Analytics ...

Collaborate with software engineers to integrate data solutions into customer-facing products and internal systems. What We're Looking For * 5-8 years of experience in Data Engineering, Analytics ...

The person in this role works closely with the Business Solutions Architect, application teams, and ... They develop and maintain data pipelines that meet the requirements of predictive models and design ...

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Data Solutions Developer information

What are the key skills and qualifications needed to thrive as a Data Solutions Developer?

To thrive as a Data Solutions Developer, you need strong programming skills (such as Python, SQL, or Java), a solid understanding of data architecture, and typically a degree in computer science or a related field. Familiarity with data warehousing tools, ETL processes, cloud platforms (like AWS or Azure), and certifications such as Microsoft Certified: Azure Data Engineer Associate are highly valued. Analytical thinking, problem-solving, and effective communication help you collaborate with stakeholders and translate business requirements into technical solutions. These skills ensure the delivery of robust, scalable data solutions that drive informed decision-making and business success.

How does a Data Solutions Developer typically collaborate with data analysts and business stakeholders?

As a Data Solutions Developer, collaboration with data analysts and business stakeholders is integral to delivering effective data-driven solutions. You will frequently engage in requirements-gathering sessions to understand business needs, translate those needs into technical specifications, and iterate on data models or pipelines based on feedback. Regular meetings and clear communication are essential to ensure the solutions you develop align with business goals and analytics objectives. Additionally, you may provide technical guidance to analysts on data access or usage and help stakeholders interpret results from the systems you build.

What is the difference between Data Solutions Developer vs Data Engineer?

AspectData Solutions DeveloperData Engineer
Primary FocusDesigning and developing data solutions and applicationsBuilding and maintaining data pipelines and infrastructure
Skills & CertificationsSQL, programming, data modeling, cloud platformsETL, database systems, cloud services, scripting
Work EnvironmentCollaborates with data analysts, developers, and business teamsWorks on data architecture, infrastructure, and backend systems
Industry UsageUsed across industries for data application developmentPrimarily in data-heavy sectors like tech, finance, and healthcare

While both roles involve working with data, Data Solutions Developers focus on creating data applications and solutions, whereas Data Engineers concentrate on building the data infrastructure and pipelines. Understanding these differences helps in choosing the right career path or job role.

What does a data solutions developer do?

A data solutions developer designs, develops, and implements data management and analytics solutions to help organizations process and interpret large datasets. They often work with programming languages like SQL, Python, or Java, and use tools such as data warehouses and ETL processes to create efficient data workflows. Their role involves collaborating with stakeholders to understand data needs and ensuring solutions are scalable and secure.

What are popular job titles related to Data Solutions Developer jobs in Montreal, QC?

For Data Solutions Developer jobs in Montreal, QC, the most frequently searched job titles are:

What job categories do people searching Data Solutions Developer jobs in Montreal, QC look for?

The top searched job categories for Data Solutions Developer jobs in Montreal, QC are:

Infographic showing various Data Solutions Developer job openings in Montreal, QC as of August 2026, with employment types broken down into 87% Full Time, 8% Part Time, and 5% Contract. Highlights an 76% Physical, 4% Hybrid, and 20% Remote job distribution.

AI Solutions Developer

Montreal, QC • On-site

Ts Imagine
Finance and Insurance • 201 - 500 employees

Full-time

Medical, PTO

Posted 3 days ago

New


Job description

About the Role What if your users could simply ask. We're building TSIQ, an AI-powered analytics and intelligence platform that answers questions, recommends actions, and runs workflows for the people who use TS Imagine's Trading, Risk and Prime Brokerage products. As an AI Solutions Developer you'll build both the foundation and the intelligence on top of it-the data models, pipelines, and semantic layers that make our data trustworthy, and the AI agents that turn it into answers.

You'll be part of our dynamic Data & Analytics Office, a globally distributed, high-impact team that processes trillions of data points and manages our cutting-edge data lake built on Snowflake. This is an opportunity to work at the intersection of data engineering, semantic modeling, and applied AI-on a product that is being defined as you build it. We have multiple openings across levels, from intermediate through senior.

Why You'll Love This Role This position is perfect for: Data Modelers: You believe a great answer starts with a well-designed model, and you take pride in structuring data so others can trust it. Applied AI Builders: You're fluent in prompt and context engineering, and you're energized by making AI agents reliable rather than merely impressive. Analytical Minds: You enjoy delving into complex data sets and ensuring the highest quality for accurate decision-making.

Problem Framers: You're comfortable sitting with a business stakeholder, untangling a vague request, and turning it into something buildable. Storytellers: You're comfortable presenting complex data and AI-driven insights in a way that engages and excites stakeholders. Action Takers: You thrive on challenges, taking ownership of a variety of responsibilities to deliver high-quality results.

Lifelong Learners: You're always eager to step outside your comfort zone and dive into the intricacies of one of the most complex business domains. Collaborative Teammates: You possess the technical and interpersonal skills to excel in a cutting-edge software development environment. What You'll Do Design and build the data models and pipelines that power TSIQ.

Develop semantic models so that AI agents reason over trading, risk, and prime brokerage data with precision and consistency. Build, test, and iterate on AI agents using prompt engineering and context engineering. Implement guardrails, evaluation, and governance controls that keep AI agents accurate, safe, and auditable.

Deliver analytics and rapid prototypes in Streamlit to put capabilities in front of users early. Perform business analysis-gather requirements from stakeholders, translate them into technical designs, and validate that what we ship answers the real question. Collaborate with a global team of developers in a fast-paced, innovative setting.

What You Bring Strong SQL skills and hands-on experience with Snowflake. Proficiency in Python, including the ability to contribute to structured, production-grade codebases-not just notebooks. Experience designing data models and building data pipelines, including transformation frameworks such as dbt.

Semantic modeling experience-defining metrics, dimensions, and business logic that downstream consumers depend on. Practical prompt engineering and context engineering skills, with a focus on making AI outputs reliable and repeatable. Experience building AI agents and implementing guardrails to govern their behavior (a strong plus).

Streamlit or comparable experience building lightweight data applications. Business analysis skills-requirements gathering, stakeholder engagement, and documentation. Exceptional communication skills.

This role sits between business stakeholders and the platform, so clear written and verbal communication is essential. Capital markets or financial services domain experience. This is extremely important to us-understanding trading, risk, or prime brokerage workflows will set you apart.

Why Join TS Imagine. On-site role-4 days per week in our Montreal office, with 1 day of flexibility. Unlimited vacation + 3 personal days.

Annual bonus and salary review. $1,500 training budget to fuel your growth. RRSP matching (3% company contribution).

Comprehensive health insurance. Subsidized public transportation (Opus & Cie). Join a global team with 10 offices worldwide and the opportunity to make a real impact on the financial industry.

Note: This role is not remote-applicants must be based in Montreal. If you're excited by AI, rigorous about data, and ready to help build something new, we want to hear from you!