Staff Analytics Engineer

Job description

WHO WE ARE Who we are: We build technology that removes barriers blocking talent from opportunity, combining the latest advancements in AI with human judgment. How we expand access: Access isn't real if it's unaffordable. Through our sister company, Passage Funding, we provide financing for international students. What we believe: Access to opportunity should not be determined by geography, gender, or wealth. We reinvest a portion of our profits to support those cut off from education - including our Afghan program. Access is the product: We build AI that turns paperwork into decisions, and decisions into real outcomes. Our mission is bold but simple: by 2030, we aim to dismantle the barriers preventing brilliant minds from accessing the opportunities they deserve. THE ROLE We are looking for a Staff Analytics Engineer to lead the development of Passage’s analytics foundation and decision infrastructure. This role sits at the intersection of engineering, analytics, and business strategy. You will design the systems that turn operational data into reliable insights used across the company. From day one, you will work closely with leadership across engineering, growth, credit, finance, product, and operations. You will design the company’s data architecture, build pipelines and analytical models, and create the metrics that guide how Passage operates. This is a senior role with broad influence across the company. You will architect the analytics layer of the data platform, ensure the quality and reliability of decision data, and help establish best practices for how the organization uses data to operate and grow. As Passage scales, you will help shape the long-term data strategy and play a key role in building the analytics function. We are a lean, high-ownership team that moves quickly. There is no fixed hierarchy and no ceiling on growth. We are looking for someone excited to build the data brain of the company, establish best practices, and eventually help grow the data team as Passage scales. WHAT YOU WILL DO BUILD THE DATA AND ANALYTICS FOUNDATION - Design and own the analytics layer of Passage’s data platform - Develop scalable data models and transformation layers that power analytics across the company - Define the company’s canonical metrics and ensure consistency across teams - Build dashboards and analytical frameworks used by leadership to evaluate performance and make business decisions - Work with data engineering to ensure reliable pipelines and data availability - Unify data across growth, product, lending, finance, and operations into a consistent analytics layer - Establish standards for data quality, monitoring, and metric governance ENABLE COMPANY-WIDE DECISION MAKING - Build dashboards and analytical tools used by leadership to monitor performance - Analyze lending performance, borrower outcomes, underwriting results, and operational workflows - Translate complex datasets into clear insights that guide strategic decisions - Define and maintain the company’s core metrics and analytical frameworks PARTNER WITH LEADERSHIP AND ACROSS COMPANY - Work directly with leaders across growth, credit, finance, product, and operations - Help teams frame analytical questions and design data-driven solutions - Establish analytical frameworks that guide how the company evaluates performance - Translate business questions into structured analytical solutions - Help teams adopt a data-driven approach to decision-making ESTABLISH ANALYTICS BEST PRACTICES - Define standards for data modeling, documentation, and metric governance - Improve data quality and reliability across operational systems - Help the company adopt a disciplined, data-driven culture SHAPE THE FUTURE OF THE DATA FUNCTION - Contribute to Passage’s long-term data and analytics strategy - Help define the future structure of the analytics and data organization - Mentor analysts and engineers as the data team grows QUALIFICATIONS - Bachelor’s degree in computer science, engineering, statistics, mathematics, or a related technical field - 6–10+ years of experience in analytics engineering, data engineering, or advanced analytics roles - Deep expertise in SQL and working with large operational datasets - Strong experience designing analytical data models and transformation pipelines - Proficiency in Python for data analysis and data processing - Experience building dashboards and decision frameworks used by leadership teams - Proven ability to translate business questions into scalable analytical solutions - Ability to operate independently and lead complex initiatives in a startup environment NICE TO HAVE - Experience working in fintech, lending, financial services, or international education - Experience analyzing loan portfolios or credit datasets - Experience working with GraphQL-based systems or API-driven data pipelines - Experience with BI tools such as Metabase or similar analytics platforms - Experience building an analytics platform from scratch at a startup - Experience mentoring analysts or contributing to the growth of a data function LOCATION Passage operates with an in-office working model. Candidates must be based in Toronto or open to relocating and working five days per week in our Toronto office. READY TO JOIN US? We are building a company designed to expand access to life-changing opportunities around the world. If you are excited about building systems, solving complex problems, and shaping how a company makes decisions, we would love to meet you. Note: Artificial intelligence may be used in the screening or assessment of applicants. If your experience does not match every requirement but you believe you can thrive in this role, we encourage you to apply. Compensation C$150K to C$200K + Offers Equity