About The JobTS Imagine builds the trading and analytics infrastructure that powers some of the largest buy‐side and sell‐side institutions in the world. We are looking for a Lead Quantitative Snowflake Developer to join our Models and Quantitative Data team in Montreal — the senior technical anchor who owns the data foundations behind TradeSmart, our execution and trading analytics platform.You will build the quantitative datasets, AI pipelines, and analytics that detect signals, identify liquidity, evaluate best execution, benchmark transaction costs, and surface alpha opportunities across equities, credit, FX, fixed income, commodities, crypto, and their derivatives.This is big data at scale. We work with trillions of price interactions, full‐depth order book history, and global multi‐asset tick data — the kind of volume where every architectural decision matters.Why this role is differentWe are an AI‐First organization. We always try to use AI first. If it does not make sense or does not work, we do differently. Since 2023, we have managed humans and digital agents as one team — not a future‐state aspiration, our operating model. Every workflow you build will be designed to be executed, evaluated, and extended by both people and agents.Reference Implementation for Snowflake and its AI Capabilities. We are one of the major consumers of Snowflake Cortex Code globally. We collaborate directly with Snowflake's product and research organizations as a design partner on Cortex Code, Cortex Analyst, Semantic Views, and AI Observability.Time‐series at real‐time scale with OneTick. We leverage OneTick from One Market Data for large‐scale time‐series analytics performed in real‐time — tick‐level market microstructure, intraday execution analysis, and live signal computation across global venues.State‐of‐the‐art stack, used daily: Snowflake, dbt, Python, SQL, Claude, OpenAI, Cortex Code, TruLens, OneTick. Not pilots.



Production workflows that ship to the largest trading firms in the world.TradeSmart focus. Execution analytics, liquidity discovery, best‐execution evaluation, transaction cost benchmarks, alpha signals. The data and AI you build directly shape how our clients trade.Built for engineers who like hard problems. Trillions of rows. Real‐time constraints. Multi‐asset complexity. If applied mathematics at scale is what you want to spend your time on, this is the role.Who Will Love This JobA scientist — loves applied mathematics and numerical problems solved at scaleAn engineer — cares about performance, clean code, and architecture that scales to trillions of rowsA data & AI practitioner — treats Claude, Cortex Code, and agentic workflows as core tools — not noveltiesAn owner — takes a broad surface area and holds themselves to a high barA leader — earns trust. Makes the engineers around them betterA learner — ready to take on some of the hardest problems in quantitative tradingWhat You'll DoOwn end‐to‐end development of scalable pipelines feeding TradeSmart's execution analytics, liquidity models, best‐execution evaluation, signal detection, and transaction cost benchmarks across all asset classesBuild and maintain high‐performance data applications in Python, SQL, Snowflake, dbt, and OneTick to transform and validate trillions of market and trade data pointsConstruct and maintain the quantitative datasets — venue liquidity profiles, execution benchmarks, intraday market microstructure features, alpha signals — that power in‐trade and post‐trade analyticsDesign and operate real‐time time‐series workflows on OneTick for tick‐level analytics,



intraday computation, and live signal generationPartner with Quant Developers and the AI Engineering team to optimize analytics infrastructure for latency, throughput, and reliability at scaleBuild agentic AI workflows using Cortex Code, Claude, and OpenAI to enhance data quality, anomaly detection, signal discovery, and quantitative research velocityDesign Snowflake Semantic Views that make trading data discoverable and queryable by both human analysts and AI agentsApply AI evaluation discipline (TruLens, Snowflake AI Observability, Agent GPA) to every agentic workflow you shipDocument data methodologies clearly to support internal review and external client validationMentor junior team members and help set the technical standards for the teamWhat You Should HaveM.S. in mathematics, physical sciences, computer science, or engineering — or equivalent practical experience5+ years of large‐scale Python development, SQL programming, and data‐intensive product work in a financial contextStrong proficiency with Snowflake and dbtWorking understanding of market microstructure, execution analytics, or trading data — and the appetite to go deeperExperience with tick‐level or time‐series data platforms (OneTick, kdb+, or equivalent) is a robust plusHands‐on experience applying AI and ML to financial data problems; familiarity with Claude, OpenAI, or comparable LLM tooling is a strong plusExperience leading technical projects and mentoring engineersWhy TS ImagineUnlimited vacation + personal daysAnnual bonus and salary review$1,500 training budgetRRSP with company matchingHealth insurancePublic transportation subsidyAbout TS ImagineTS Imagine delivers integrated trading, portfolio and risk solutions used by global financial institutions.With 400 employees across 10 offices, we power workflows across front, middle and back office.We challenge our people to innovate, move fast, and think differently. #J-18808-Ljbffr

📌 Lead Quantitative Snowflake Developer (Montreal)
🏢 TS Imagine
📍 Montreal