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Snowflake Jobs in Quebec (NOW HIRING)

Votre quotidien d'un developpeur Snowflake chez Crakmedia impliquera de : * Concevoir et developper les chaines de traitements conformement a l'architecture ETL etablie en collaboration avec les ...

... Snowflake In this role you will be instrumental in designing developing and deploying robust Power BI solutions that empower our stakeholders with critical business intelligence Your expertise in ...

Data Developer II

Sherbrooke, QC · On-site

CA$35.06 - CA$46/hr

Design, develop, and maintain modern data pipelines, data warehouses, and data lakes using Snowflake and Azure Data Services. * Architect data solutions leveraging DBT for data transformation and ...

Design, develop, and maintain modern data pipelines, data warehouses, and data lakes using Snowflake and Azure Data Services. * Architect data solutions leveraging DBT for data transformation and ...

Contribute to the evolution of distributed architectures and data pipelines using DataIQ, Databricks and Snowflake ; * Participate in the automation of monthly and weekly processing using Python and ...

Contribuer a l'evolution d'architectures distribuees et de pipelines de donnees utilisant DataIQ, Databricks et Snowflake ; * Participer a l'automatisation des traitements mensuels et hebdomadaires a ...

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Snowflake information

See Quebec salary details

$15

$69

$100

How much do snowflake jobs pay per hour?

As of Jul 5, 2026, the average hourly pay for snowflake in Quebec is $69.28, according to ZipRecruiter salary data. Most workers in this role earn between $58.89 and $78.61 per hour, depending on experience, location, and employer.

What are some common challenges faced by Snowflake professionals, and how can they be addressed?

Snowflake professionals often encounter challenges such as optimizing query performance, managing data security and access controls, and integrating Snowflake with multiple data sources. Addressing these challenges requires continuous learning about the platform’s evolving features, proactively monitoring query and storage usage, and collaborating closely with data architects, DevOps, and IT security teams. Staying up to date with best practices and regularly attending Snowflake community webinars or training can also be extremely helpful. Most companies encourage knowledge sharing and collaboration, so being proactive in problem-solving will help you thrive in this role.

Is Snowflake a good career?

A career as a Snowflake professional typically involves working with cloud data platforms, data warehousing, and SQL skills. It offers opportunities in data engineering, analytics, and cloud computing, with demand driven by the growth of data-driven decision making. Certifications and experience with cloud environments can enhance job prospects in this field.

What is a Snowflake job?

A Snowflake job typically refers to tasks executed within Snowflake, a cloud-based data platform. These jobs can include data loading, transformation, querying, or scheduled tasks using Snowflake's task and stream features. They help automate data workflows, improve performance, and ensure efficient data management within the Snowflake ecosystem.

How much do Snowflake employees make?

Salaries for Snowflake employees vary by role, experience, and location, but the average base salary ranges from approximately $100,000 to $150,000 annually for many positions. Technical roles such as data engineers and software engineers tend to be higher, often exceeding $120,000, with additional compensation like bonuses and stock options common in the company’s compensation packages.

Is Snowflake skill in demand?

Snowflake skills are highly in demand as organizations increasingly adopt cloud data warehousing solutions. Professionals with expertise in Snowflake, along with knowledge of SQL and data management, often find strong job opportunities across various industries.

How hard is it to get a job at Snowflake?

Getting a job as a Snowflake professional typically requires relevant technical skills such as data warehousing, SQL, and cloud platforms, along with experience in data management or analytics. The hiring process often involves multiple interview rounds assessing technical knowledge, problem-solving ability, and cultural fit, making it competitive but achievable with proper preparation.

What are the key skills and qualifications needed to thrive in the Snowflake position, and why are they important?

To thrive as a Snowflake professional (such as a Snowflake Data Engineer or Administrator), you need a solid understanding of cloud data warehousing, SQL, and data modeling, typically supported by a degree in computer science or related fields. Experience with the Snowflake platform, data integration tools (like Informatica or Talend), and relevant certifications such as SnowPro are highly valuable. Strong problem-solving abilities, communication skills, and adaptability help professionals translate business requirements into data solutions and work effectively with cross-functional teams. These competencies are crucial for optimizing data workflows, ensuring system performance, and supporting the data-driven goals of an organization.

What are the most commonly searched types of Snowflake jobs in Quebec? The most popular types of Snowflake jobs in Quebec are:
What are popular job titles related to Snowflake jobs in Quebec? For Snowflake jobs in Quebec, the most frequently searched job titles are:
What job categories do people searching Snowflake jobs in Quebec look for? The top searched job categories for Snowflake jobs in Quebec are:
Infographic showing various Snowflake job openings in Quebec as of June 2026, with employment types broken down into 51% Part Time, and 49% Contract. Highlights an 77% Physical, 6% Hybrid, and 17% Remote job distribution, with an average salary of $144,104 per year, or $69.3 per hour.
Lead Quantitative Snowflake Developer

Lead Quantitative Snowflake Developer

Ts Imagine

Montreal, QC

Full-time

Medical, Retirement, PTO

Posted 16 days ago


Job description

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.