Senior Data Engineer

Job description

This posting reflects a current, actively recruited opening at Float. All applications are being reviewed on a rolling basis. ABOUT FLOAT Float is on a mission to simplify finance for Canadian businesses, empowering them to eliminate complexity and unlock new opportunities. Through our innovative platform, Float enables businesses to streamline financial operations and optimize cash flow, so they can focus on what matters most: growth. As one of Canada’s fastest growing companies https://www.theglobeandmail.com/business/rob-magazine/top-growing-companies/article-ranking-canadas-top-growing-companies-of-2024/ and top-rated startups in 2025 https://www.linkedin.com/posts/floatfinancial_were-proud-to-share-that-float-has-been-activity-7387093684720300032-2DDz/, 2024 https://www.linkedin.com/pulse/linkedin-top-startups-2024-15-canadian-companies-rise-linkedin-news-llihe/ and 2023 https://lnkd.in/TSU23CA, Float is customer-obsessed, passionate and entrepreneurial, with a team that includes leaders from Uber, Stripe, Shopify, Top Hat, Ada, Doordash, Snowflake, and Wealthsimple. At Float, everyone is an owner, bringing their unique perspective to our team and product. Your voice is important, and we take having a culture based on feedback seriously. We openly share our thoughts and differing opinions so we can continue to improve. We do our best to keep our decision-making decentralized so that all team members feel ownership in our success. OUR PRODUCT Float is Canada’s intelligent financial operating system, combining modern financial services and software to help businesses spend, save, and grow. Trusted by more than 10,000 Canadian companies, Float provides high-limit corporate cards, automated expense management, next-day bill payments, high-yield accounts, and industry-leading support, all built in Canada, for Canada. Float recently announced our $85 million Series C https://floatfinancial.com/press/float-financial-raises-cad-85-million-series-c, and is backed by world-class investors, including Inovia Capital, Growth Equity at Goldman Sachs Alternatives, OMERS Ventures, and Silicon Valley Bank. Our team is a collection of ambitious, collaborative and mission-driven people from all walks of life but with one goal: helping Canadian companies not just survive but thrive. And we’re looking for bold innovators to help shape the future of business finance in Canada. AI USE IN OUR HIRING PROCESS We use technology, including artificial intelligence (AI), to support parts of our hiring process. This may include AI-assisted scheduling and candidate communications, and AI-generated interview notes, guides or summaries to help our team focus on the conversation. All hiring decisions are made by our hiring team. ABOUT THE ROLE This is Float's first dedicated data engineering hire. You'll own the Snowflake architecture and ingestion layer end-to-end — the plumbing that carries data from banking partners, card processors, CRM, marketing platforms, and product systems into one clean, reliable, well-governed place. You'll work closely with our Analytics Engineer, who owns the dbt and transformation layer, and be the infrastructure backbone our Data Scientists and growing analytics team depend on. Together, you and the Analytics Engineer form the core of a data platform the rest of Float can trust and build on. We're at an inflection point. Growing transaction volumes and an expanding product surface mean there's real work to do — and you'll have the scope and ownership to do it properly. WHAT YOU'LL BE DOING - Own Float's Snowflake architecture end-to-end — organization, cost efficiency, and access controls - Design and build a real orchestration layer for our ingestion pipelines, replacing ad hoc processes - Stand up observability and alerting so pipeline failures and data staleness are caught immediately, not downstream - Introduce data contracts between producer and consumer systems, so upstream changes (new payment rails, new banking products, vendor field changes) stop silently breaking things - Own the data reliability layer — establish CI/CD pipelines for data code, build data quality checks directly into pipelines, and orchestrate jobs that live outside of ingestion and dbt (ML pipelines, data quality runs, operational workflows), so everything is tested, automated, and deployed consistently - Partner closely with our Analytics Engineer to keep the ingestion → transformation handoff clean and dependable — and collaborate on lineage tracking and metadata tooling so the broader team has visibility into where data comes from and how it flows - Develop, document and socialize a target-state data architecture and phased migration roadmap, in partnership with data and engineering leadership. - Build and maintain the data pipelines that power ML model training and inference — ensuring the data science team has reliable, well-structured feature data for ML use cases - Leverage AI tooling across the full engineering lifecycle — from writing and reviewing pipeline code to accelerating observability, anomaly detection, and incident triage - Partner with product and infrastructure engineering to maintain consistent telemetry standards across Float's codebases, ensuring product events flow reliably into the data platform. WHAT SUCCESS LOOKS LIKE (6–12 MONTHS) In your first 30 days, you're not building — you're mapping. You'll talk to the Analytics Engineer, the data scientists, and engineering stakeholders to understand what exists and what's broken — but also to finance, ops, and product teams to understand where data is and isn't being trusted across the business. By 60 days, you've stabilized the most urgent issues and produced a draft target architecture and prioritized roadmap — signed off with data and engineering leadership. By 90 days, you're executing: an orchestration layer, observability and alerting, and initial data quality checks on the most critical pipelines are in place. Longer term, success looks like: - Data the business trusts — analysts, data scientists, and stakeholders make decisions with confidence - Pipelines with defined SLAs, clear ownership, and no silent failures - A Snowflake environment that's intentional and cost-controlled - Data contracts covering the large majority of critical sources, with a clear registry of what's covered - An analytics engineering and data science team that's unblocked — focused on modeling and insight - Infrastructure that scales with Float's next product launch WHAT WE'RE LOOKING FOR - Genuine proficiency in Python and SQL — not just functional, but strong - Hands-on experience building and owning ELT/ETL pipelines at scale - Deep experience with a modern cloud data platform (Snowflake, Databricks, or equivalent), including architecture, cost optimization, and access controls - Real orchestration experience and a clear point of view on how to use it well - dbt fluency — you won't own the transformation layer, but you'll work seamlessly with the person who does - Practical experience implementing data observability, data quality frameworks, and data contracts — not just familiarity with the concepts, but having actually put them in place - A track record of looking at a messy data environment and developing a clear, pragmatic point of view on what good looks like — and how to get there without over-engineering - You've built something from scratch in a high-ownership environment - You communicate clearly with non-technical stakeholders, earn trust across a business, and hold your technical opinions strongly but loosely - You use AI tooling deliberately and daily — for coding, for monitoring, and for triage — and you have a clear point of view on where it genuinely accelerates your work and where it doesn't - Nice to Haves: - Experience with data governance and compliance in a regulated environment - Fintech or payments background — understanding how transaction, card, and banking data behaves You'll thrive here if you're energized by ambiguity, default to action, hold strong opinions loosely, and take real pride in building things properly. This role is best suited to builders who own outcomes — not people who execute tasks assigned to them. OUR HIRING PHILOSOPHY We hire for character, curiosity, and learning velocity before credentials. Titles matter less than impact, and every hire is expected to raise the bar for Float as a whole. WHY YOU SHOULD JOIN - Work at one of Canada's fastest-growing fintech companies - Make a real impact in a high-autonomy, high-growth role - Collaborate with an ambitious and supportive team - Competitive compensation, equity options, and benefits - Hybrid work model – we are based in Toronto with in-office days for connection and collaboration - Enjoy catered team lunches every Tuesday, Wednesday and Thursday - Bring your pup to our dog-friendly office - Thrive in a high-trust, high-performance culture where your work truly matters IN SHORT At Float, you’ll thrive if you’re bold, curious, and eager to make a real impact. We're building something special—and having a lot of fun along the way. If you’re excited to build, grow, and win together, we’d love to meet you. We’re committed to building a workplace that’s welcoming and accessible for everyone. If you need any accommodations during the hiring process or once you join Float, just let us know! You can reach out to Vic https://www.linkedin.com/in/victoria-boult-b21b2053/ (victoria@floatfinancial.com), and we’ll work with you to make sure you have what you need to succeed.