Propel (TSX: PRL) is the fintech company building a new world of financial opportunity by facilitating access to credit for consumers underserved by traditional financial institutions. Through its AI-driven platform, Propel evaluates customers in a more comprehensive way than traditional credit scores can. Our revolutionary fintech platform has already helped consumers access over one million loans and lines of credit and over one billion dollars in credit. To build a new world of opportunity we bring together the brightest talent to help us build opportunities. We are entrepreneurs and believe in measuring success through results and growing within; talent and hard work never goes unnoticed. At Propel, we are here to change the way employees, customers and shareholders succeed together. We are a team of passionate entrepreneurs, who foster curiosity and growth in our employees. Our culture is why we have been so successful and why our employees choose Propel to build their careers. It is also why we are one of North America's fastest growing companies and a Best Place to Work. Join us as we change the way employees, customers and shareholders succeed together. About You: You thrive in a vibrant, entrepreneurial organization where your ideas are valued. You are motivated by goals, a self-starter, and enjoy wearing multiple hats in a fast-growing fintech environment. You are a talented professional looking for a career, not a job. Reporting to the Director, Data Platform, you will be responsible for developing and troubleshooting Stored Procedures, SQL, and SQL-based strategy for various teams. Much of your work will focus on Finance-related concepts and you will work closely with our Finance team, so ideally you already have some of this knowledge or you are highly motivated and autonomous when learning. Responsibilities Design, develop, and maintain secure, scalable Snowflake databases, schemas, warehouses, and data-sharing solutions for analytics, reporting, and finance use cases Translate business and Finance requirements into well-defined Snowflake data models, technical designs, data contracts, and implementation plans Develop and troubleshoot advanced Snowflake SQL,



Snowflake Scripting, stored procedures, user-defined functions, and reusable data-platform components Build and maintain reliable ELT pipelines using Snowflake stages, file formats, COPY INTO, Snowpipe, Streams, Tasks, Dynamic Tables, and appropriate integration or orchestration tools. Create and evolve dimensional, relational, and semi-structured data models using Snowflake capabilities such as VARIANT, FLATTEN, and schema evolution where appropriate Optimize Snowflake workloads by using Query Profile and query history to improve pruning, warehouse sizing, clustering, concurrency, caching, and overall execution performance Establish cost-efficient warehouse and workload-management strategies, including sizing, auto-suspend, resource monitors, and usage monitoring Implement and maintain Snowflake security and governance controls, including role-based access control, least-privilege permissions, masking policies, row access policies, tagging, auditing, and data classification Support reliable development and release practices across environments through Git-based version control, code review, automated testing, CI/CD, and repeatable deployment processes Develop monitoring, reconciliation, quality checks, and operational dashboards to identify pipeline failures, data freshness issues, query regressions, and unexpected Snowflake consumption Apply Snowflake capabilities such as Time Travel, zero-copy cloning, secure data sharing, and environment isolation to support recovery, testing, and controlled access Partner with Finance, Data Engineering, Analytics, and application teams to resolve data issues, improve definitions, and increase trust in critical business data Document data models, lineage, operational procedures, security decisions,



and performance or cost-tuning recommendations Contribute to technical standards and mentor team members on Snowflake engineering best practices Requirements Must Have: 5+ years of professional experience designing, developing, and troubleshooting SQL-based database or data-engineering solutions 3+ years of hands-on experience building and operating production workloads on Snowflake Solid knowledge of Snowflake architecture, including databases, schemas, virtual warehouses, micro-partitions, storage/compute separation, caching, and workload isolation Advanced Snowflake SQL skills, including complex transformations, window functions, semi-structured data, query optimization, and data reconciliation Practical experience designing ELT pipelines with Snowflake stages, file formats, COPY INTO, Snowpipe, Streams, Tasks, Dynamic Tables, or comparable Snowflake-native features Proven ability to model data for analytics and Finance, including dimensional modeling, facts and dimensions, slowly changing dimensions, and appropriate normalization or denormalization decisions Demonstrated experience diagnosing and improving Snowflake performance using query history, Query Profile, warehouse configuration, partition pruning, clustering, and workload/concurrency analysis Experience managing Snowflake access and governance through RBAC, custom roles, grants, masking policies, row access policies, tags, and audit or usage monitoring Experience with Python and scripting for data engineering, automation, testing, or Snowflake administration; Snowpark experience is an asset Experience with GitHub or GitLab and collaborative software-development practices, including pull requests, code review, and automated deployment Experience using generative AI tools such as ChatGPT, Claude, or Copilot is an asset, along with the ability to adopt AI tools responsibly in day-to-day engineering work Nice To Have: Experience with dbt, Airflow, Dagster, or another modern transformation and orchestration framework integrated with Snowflake Experience with Snowflake governance, observability, cost-management, data-quality, or catalog tools Experience with Snowflake

📌 Sr. Data Engineer (Toronto)
🏢 Propel Holdings
📍 Toronto