Lead Quantitative Data Developer (Snowflake)

✦ About the Position TS Imagine develops trading and analytics infrastructures that power some of the world's largest buy-side and sell-side institutions. We are looking for a Lead Quantitative Data Developer (Snowflake) to join our Quantitative Models & Data team in Montreal—a key senior technical leadership role responsible for the data foundations of TradeSmart, our execution and trading analytics platform.

You will be responsible for designing quantitative data sets, AI pipelines, and analytical solutions to detect signals, identify liquidity, evaluate best execution, benchmark transaction costs, and reveal alpha opportunities across equities, credit, FX, fixed income, commodities, cryptoassets, and their derivatives.

This is massive, large-scale data. We process trillions of price interactions, complete order book history, and multi-asset tick data globally—where every architecture decision has a critical impact.

✦ Why This Role is Different

We are an AI-First Organization

We always look to use artificial intelligence first. When it is not relevant or does not work, we adopt another approach. Since 2023, we have been running humans and digital agents as a single team—not a future vision, but our current operational model. Every workflow you design is intended to be executed, evaluated, and enriched by both people and agents.

A Reference Implementation for Snowflake and Its AI Capabilities

We are among the largest users of Snowflake Cortex Code globally. We collaborate directly with Snowflake's product and research teams as a design partner on Cortex Code, Cortex Analyst, semantic views, and AI observability.

Real-Time Time Series Analysis with OneTick

We use OneTick (One Market Data) for large-scale real-time time series analysis—market microstructure at the tick level, intraday execution analysis, and live signal calculation across global markets.

A Cutting-Edge Tech Stack, Used Daily

Snowflake, dbt, Python, SQL, Claude, OpenAI, Cortex Code, TruLens, OneTick. These are not pilot projects but production workflows used by the world's largest trading institutions.

Focus on TradeSmart

Execution analysis, liquidity detection, best execution evaluation, transaction cost benchmarks, alpha signals. The data and AI solutions you develop directly impact how our clients trade.

Designed for Engineers Who Love Complex Challenges

Trillions of data lines. Real-time constraints. Multi-asset complexity. If you want to work on large-scale applied mathematics, this role is for you.

✦ Profile Sought

• A scientific profile—passionate about applied mathematics and solving large-scale numerical problems
• An engineer—attentive to performance, code quality, and architectures capable of handling trillions of lines
• A data & AI practitioner—who considers Claude, Cortex Code, and agentic workflows as essential tools, not just novelties
• An autonomous profile—capable of taking ownership of a broad scope and maintaining a high standard
• A leader—who inspires confidence and elevates the technical level of the team
• A learner—ready to tackle some of the most complex challenges in quantitative trading
• ✦ What You Will Do
• Ensure the end-to-end development of scalable data pipelines feeding TradeSmart's execution analysis, liquidity models, best execution evaluation, signal detection, and transaction cost benchmarks across all asset classes
• Design and maintain high-performance data applications in Python, SQL, Snowflake, dbt, and OneTick to transform and validate trillions of market and transaction data points
• Build and maintain quantitative data sets—platform liquidity profiles, execution benchmarks, intraday market microstructure features, alpha signals—that fuel ongoing and post-trade analyses
• Design and operate real-time time series workflows on OneTick for tick-level analysis, intraday calculations, and live signal generation
• Collaborate with Quant Developers and the AI Engineering team to optimize analytical infrastructures in terms of latency, throughput, and large-scale reliability
• Develop agentic AI workflows using Cortex Code, Claude, and OpenAI to improve data quality, anomaly detection, signal identification, and quantitative research productivity
• Design semantic Snowflake views to make trading data accessible and queryable by both human analysts and AI agents
• Apply AI evaluation methodologies (TruLens, Snowflake AI Observability, Agent GPA) to every agentic workflow developed
• Clearly document data methodologies to support internal reviews and external validation with clients
• Mentor junior team members and contribute to defining technical standards
• ✦ Skills You Must Have
• M.S. in mathematics, physical sciences, computer science, or engineering—or equivalent practical experience
• 5+ years of experience in large-scale Python development, SQL programming, and data-intensive product development in a financial context
• Strong proficiency in Snowflake and dbt
• Solid understanding of market microstructure, execution analysis, or trading data—and willingness to deepen these knowledge areas
• Experience with tick-level or time series data platforms (OneTick, kdb+, or equivalent) is highly appreciated
• Practical experience applying AI and machine learning to financial data problems; familiarity with Claude, OpenAI, or comparable LLM tools is a significant plus
• Experience leading technical projects and mentoring engineers
• ✦ Why Join TS Imagine?
• Unlimited vacation + personal days
• Annual bonus and salary review
• $1,500 training budget
• REER with employer contribution
• Health insurance
• Transit subsidy

Note: This position is not remote—candidates must be based in Montreal or the surrounding area!

✦ About TS Imagine TS Imagine offers integrated trading, portfolio management, and risk management solutions used by global financial institutions.

With approximately 400 employees spread across 10 offices, we power front, middle, and back-office operations.

We encourage our teams to innovate, move quickly, and think differently.