Senior Data Developer

AI Platform & Data Engineering builds and operates the data platform behind TS Imagine’s trading, risk, and AI capabilities.The team brings external and internal data into Snowflake and maintains the shared engineering foundations used across the business: data ingestion, transformation, distribution, monitoring, data quality, regression testing, and production support. We work with complex financial datasets, including instrument reference data, pricing, common data, and corporate actions.As a Senior Data Engineer, you will own production data systems built with Snowflake, dbt, SQL, and Python. You will help modernize established pipelines, improve the platform’s shared capabilities, and contribute to the data and semantic foundations behind TSIQ, TS Imagine’s natural-language AI interface for intelligence and agentic workflows.What you’ll do
Design, build, and operate pipelines that ingest, validate, transform, and distribute data from vendors, internal systems, APIs, and files.Develop and maintain dbt models and Snowflake data structures supporting trading, risk, analytics, and operational workflows.Build production Python for data ingestion, integrations, orchestration, and engineering tooling.Improve the frameworks used for monitoring, data quality, regression testing, and incident diagnosis.Build and maintain data models and semantic views used by downstream applications and AI interfaces.Investigate production data issues, identify root causes, and implement lasting fixes.Contribute to technical design, code review, engineering standards, and delivery practices.Help other teams adopt effective approaches to building and operating data pipelines on the shared platform.What we’re looking for
Five or more years of relevant data engineering experience, including ownership of production data systems.Strong SQL skills, including data modeling, query design, performance awareness, and debugging complex transformations.Strong Python skills and experience developing maintainable, tested, multi-module applications.Hands-on production experience with Snowflake and dbt.Experience integrating APIs, databases, flat files, or event-driven data sources.Practical knowledge of data quality, monitoring, failure handling, and production support.Experience with Git, code review, automated testing, and CI/CD.Sound engineering judgment: able to balance delivery speed, system complexity, operating cost, and maintainability.Interest in applying AI tools thoughtfully as part of the engineering workflow.Useful experience, but not requiredFinancial-market data, including security master, instrument reference data, pricing, risk, or corporate actions.Semantic modeling or governed analytics layers.Asynchronous Python and API-heavy ingestion services.Modernizing legacy pipelines or stored-procedure-based data systems.About the team
AI Platform & Data Engineering is part of TS Imagine’s approximately 40-person AI & Data Engineering organization, with colleagues across North America, EMEA, and APAC. The wider group brings together data engineers, data scientists, quantitative engineers, AI engineers, data analysts, and data stewards.The team works closely with product, risk, client service, and other engineering teams. Its role is both hands-on and enabling: operating core data capabilities while helping other teams build against them effectively.Why TS Imagine?
Hybrid work model: four days in the Montreal office.Unlimited vacation plus three personal days.Annual bonus and salary review.$1,500 annual training budget.RRSP matching with a 3% company contribution.Subsidized public transportation through Opus & Cie.Work on production systems used by global capital-markets clients.This is not a remote role. Applicants must be based in Montreal and able to communicate in French.About TS Imagine
TS Imagine provides integrated trading, portfolio, and real-time risk solutions for capital markets. Formed from TradingScreen and Imagine Software, the company serves approximately 500 buy-side and sell-side institutions globally, including hedge funds, asset managers, pension funds, mutual funds, and financial institutions.
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