Lead Snowflake Developer

GuruLink; Montreal (administrative region); On-site; CAD 90,000 - 120,000; Full time

Job summary

GuruLink is looking for a skilled data engineer in Montreal, Quebec, to develop scalable analytics pipelines across multiple asset classes. You will own the end-to-end development, building high-performance applications in Python and SQL while mentoring junior team members.

The role requires significant experience in financial data environments, proficiency with Snowflake, and strong programming skills. Join GuruLink's commitment to innovate in the Fixed Income market!

Qualifications

• 7+ years of large-scale Python development, SQL programming, and data-intensive product work in finance.
• Strong proficiency with Snowflake and dbt.
• Experience with tick-level or time-series data platforms is a strong plus.

Responsibilities

• Own end-to-end development of scalable pipelines for analytics and liquidity models.
• Build and maintain high-performance data applications to transform market data.
• Design and operate real-time time-series workflows for analytics and signal generation.

Skills

Large-scale Python development

SQL programming

Data-intensive product work

Strong proficiency with Snowflake

Experience with tick-level or time-series data

Education

BSc in mathematics, physical sciences, computer science, or engineering

Tools

Python

SQL

Snowflake

OneTick

Job description

Location: Montreal, Quebec

Our client is the leading global provider of multi-asset trading systems to the buy‑side, sell‑side and trading platforms, accelerating the technical evolution of the Fixed Income market by developing connectivity, integration and data normalization to institutional investors, dealers and trading platforms. Providing global coverage from offices in New York, London, Paris, Frankfurt, Geneva, Hong Kong, Singapore and Tokyo.

This Role

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.

Responsibilities

• Own end‑to‑end development of scalable pipelines feeding 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
• 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
• 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

Must Have Skills

• BSc in mathematics, physical sciences, computer science, or engineering, or equivalent practical experience
• 7+ years of large‑scale Python development, SQL programming, and data‑intensive product work in a financial context
• Strong proficiency with Snowflake and dbt
• Experience with tick‑level or time‑series data platforms (OneTick, kdb+, or equivalent) is a strong plus
• Familiarity with Claude, OpenAI, or comparable LLM tooling is a strong plus
• Experience leading technical projects and mentoring engineers

Nice to Have Skills

• Working understanding of market microstructure, execution analytics, or trading data, and the appetite to go deeper
• Hands‑on experience applying AI and ML to financial data problems