Lead Quantitative Snowflake Developer
Lead Quantitative Snowflake Developer (Hybrid)
Location: Montreal, QC
Onsite: 4 days a week for the first 90 days, then moves to onsite 3 days after.
Position Overview
We are seeking a Lead Quantitative Snowflake Developer to design, build, and optimize data platforms that power quantitative analytics and trading research. You will lead the development of scalable Snowflake-based data architectures, implement robust ETL/ELT pipelines using dbt, and write production-quality Python and SQL to support time-series and event-driven datasets. The role combines technical ownership, hands-on engineering, and collaboration with quantitative researchers to deliver reliable, high-performance data products for analytics and modeling.
Key Responsibilities
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Lead design and implementation of Snowflake data architectures to support quantitative analytics, ensuring scalability, security, and cost-efficiency.
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Develop, maintain, and optimize ELT/ETL pipelines using dbt and SQL to transform raw market, reference, and event data into clean analytical datasets.
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Write production-grade Python and SQL for data ingestion, transformation, validation, and orchestration; implement robust testing and monitoring.
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Collaborate closely with quantitative researchers, data scientists, and engineers to translate analytical requirements into data models and pipelines.
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Optimize query performance, clustering, micro-partitioning, and storage strategies in Snowflake to meet low-latency analytics needs.
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Establish data quality, lineage and governance practices, including automated testing, documentation, and CI/CD for dbt projects.
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Mentor and lead a small team of data engineers, setting standards for best practices, code reviews, and architectural decisions.
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Build and maintain processes for handling large-scale time-series and tick-level data, including partitioning, retention, and compression strategies.
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Integrate Snowflake pipelines with orchestration tools and cloud services (e.g., Airflow, Prefect, AWS/GCP/Azure) to enable reliable job scheduling and alerting.
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Drive cross-functional initiatives to improve platform reliability, observability, and cost control, and support ad-hoc analysis and performance troubleshooting.
Qualifications
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Bachelors or Masters degree in Computer Science, Engineering, Mathematics, Statistics, Finance, or a related field.
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5+ years of experience building data platforms and pipelines, with at least 3 years of hands-on experience in Snowflake production environments.
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Expert-level SQL skills and proven experience designing complex, performant analytical queries and schemas.
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Strong Python development experience for data engineering tasks, including libraries such as Pandas, NumPy, and standard testing frameworks.
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Deep experience with dbt for data transformations, models, testing, documentation, and CI/CD workflows.
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Demonstrated experience optimizing Snowflake performance (clustering, partitioning, caching, resource monitors) and managing costs.
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Experience working with time-series or high-frequency datasets is highly desirable (nice-to-have: familiarity with time-series platforms like KDB, TimescaleDB, InfluxDB, or specialized tick-data stores).
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Familiarity with cloud platforms (AWS, GCP, or Azure), containerization, orchestration (Airflow/Prefect), and version control (Git).
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Strong communication skills and experience collaborating with quantitative teams; ability to translate business and research requirements into technical solutions.
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Leadership experience mentoring engineers, driving standards, and managing delivery of complex projects.
Benefits
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Hybrid-remote work schedule (4 days on-site)
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Unlimited vacation
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Personal days off
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Annual bonus program
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Career training program
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Retirement plan with company match
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Health insurance
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Public transportation benefits
- This job was first posted by CyberCoders on 07/01/2026 and applications will be accepted on an ongoing basis until the position is filled or closed.Everforth CyberCoders is proud to be an Equal Opportunity Employer
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, sexual orientation, gender identity or expression, national origin, ancestry, citizenship, genetic information, registered domestic partner status, marital status, status as a crime victim, disability, protected veteran status, or any other characteristic protected by law. Our hiring process includes AI screening for keywords and minimum qualifications, and a virtual recruiter as part of the application process. A human recruiter reviews all results. Click here for details on our virtual recruiter . Everforth CyberCoders will consider qualified applicants with criminal histories in a manner consistent with the requirements of applicable state and local law, including but not limited to the Los Angeles County Fair Chance Ordinance, the San Francisco Fair Chance Ordinance, and the California Fair Chance Act. Everforth CyberCoders is committed to working with and providing reasonable accommodation to individuals with physical and mental disabilities. Individuals needing special assistance or an accommodation while seeking employment can contact a member of our Human Resources team at
[email protected] to make arrangements.
