✦ About the job
TS 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 different
We 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 job
- A scientist — Loves applied mathematics and numerical problems solved at scale
- An engineer — Cares about performance, clean code, and architecture that scales to trillions of rows
- A data & AI practitioner — Treats Claude, Cortex Code, and agentic workflows as core tools — not novelties
- An owner — Takes a broad surface area and holds themselves to a high bar
- A leader — Earns trust. Makes the engineers around them better
- A learner — Ready to take on some of the hardest problems in quantitative trading
What you’ll do
- Own 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 classes
- Build and maintain high-performance data applications in Python, SQL, Snowflake, dbt, and OneTick to transform and validate trillions of market and trade data points
- Construct and maintain the quantitative datasets — venue liquidity profiles, execution benchmarks, intraday market microstructure features, alpha signals — that power in-trade and post-trade analytics
- Design and operate real-time time-series workflows on OneTick for tick-level analytics, intraday computation, and live signal generation
- Partner with Quant Developers and the AI Engineering team to optimize analytics infrastructure for latency, throughput, and reliability at scale
- Build agentic AI workflows using Cortex Code, Claude, and OpenAI to enhance data quality, anomaly detection, signal discovery, and quantitative research velocity
- Design Snowflake Semantic Views that make trading data discoverable and queryable by both human analysts and AI agents
- Apply AI evaluation discipline (TruLens, Snowflake AI Observability, Agent GPA) to every agentic workflow you ship
- Document data methodologies clearly to support internal review and external client validation
- Mentor junior team members and help set the technical standards for the team
What you should have
- M.S. in mathematics, physical sciences, computer science, or engineering — or equivalent practical experience
- 5+ years of large-scale Python development, SQL programming, and data-intensive product work in a financial context
- Strong proficiency with Snowflake and dbt
- Working understanding of market microstructure, execution analytics, or trading data — and the appetite to go deeper
- Experience with tick-level or time-series data platforms (OneTick, kdb+, or equivalent) is a strong plus
- Hands-on experience applying AI and ML to financial data problems; familiarity with Claude, OpenAI, or comparable LLM tooling is a strong plus
- Experience leading technical projects and mentoring engineers
✦ Why TS Imagine
- Unlimited vacation + personal days
- Annual bonus & salary review
- $1,500 training budget
- RRSP with company matching
- Health insurance
- Public transportation subsidy
✦ About TS Imagine
TS 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.
