This role requires working from the downtown Toronto office 4 days/week (Mon, Tues, Thurs, Fri). Candidates must be based within a 50-mile commuting distance of the office.
About the RoleAs a Finance Automation Lead at Opendoor, you will join the Finance team reporting to the President of Opendoor with a mandate to 10x our data leverage across Finance. This is a high-impact IC role at the intersection of data architecture, AI engineering, and financial systems.
Opendoor has adopted a "Default to AI" philosophy—if AI can handle it, AI should handle it. We're not theorizing about AI transformation; we're shipping it. You are a builder with a product mindset who will help transform Finance from a service function into a product—one that delivers real-time insights, automated workflows, and self-service capabilities to every team at Opendoor. You understand how LLMs work, you’ve built agents, and you understand how finance data can be leveraged and structured with these models.
Build AI-Powered Finance Infrastructure
Design and deploy AI agents that automate data fetching, analysis, reporting, and forecasting workflows
Architect data pipelines connecting financial planning systems (Adaptive) to Snowflake and downstream applications
Build semantic layers that enable non-technical finance team members to access data through natural language
Create Finance Tools & Products
Develop internal tools that transform manual finance processes into automated, scalable products
Build dashboards and self-service interfaces that eliminate analyst bottlenecks
Create systems that enable managers to answer their own headcount, budget, and forecast questions without finance intervention
Own Data Architecture for Finance
Organize finance data for best-in-class LLM capabilities
Design data models that support automated analysis, real-time querying, and AI agent interactions
Establish data quality frameworks and governance for financial systems
Drive Automation at Scale
Identify high-value automation opportunities across Finance (accruals, reporting, forecasting, variance analysis)
Implement workflow automation using tools like Gumloop, Claude, and custom-built agents
Measure and improve automation accuracy, reducing manual intervention over time
Technical Foundation
At least 3+ years of experience building data systems in a finance, analytics, or data engineering role
- Track record of building and deploying AI agents or LLM-powered applications in production environments
Advanced SQL proficiency with ability to design complex data models and optimize query performance
Production experience with Python for data engineering, automation, and AI agent development
Hands-on experience with modern data warehouses (Snowflake, BigQuery, or similar)
AI & Automation Expertise
Deep understanding of LLM capabilities, limitations, and prompt engineering best practices
Experience architecting semantic layers or natural language interfaces for data access
Familiarity with AI orchestration frameworks (LangChain, LlamaIndex, or similar)
Proven ability to identify high-ROI automation opportunities and implement end-to-end solutions
Experience with workflow automation tools and API integrations
Data Architecture & Systems Design
Strong data modeling skills with focus on enabling both human analysts and AI agents
Experience designing data pipelines that connect planning systems (like Adaptive, Anaplan) to data warehouses
Understanding of data governance, quality frameworks, and metadata management
Ability to architect scalable systems that reduce analyst bottlenecks and enable self-service
Product & Business Mindset
Builder mentality with ability to ship functional products, not just analyses
Experience translating messy business problems into clean technical solutions
Strong stakeholder management skills with ability to influence senior finance leadership
Comfort working in ambiguous, fast-moving environments with evolving requirements
Systems thinking approach to understanding complex problems and their root causes
Bonus points if you have:
Experience in fintech, real estate tech, or high-velocity transaction businesses
Background in financial planning & analysis (FP&A) or corporate finance
Familiarity with finance-specific tools (Adaptive Insights, NetSuite, etc.)
Our compensation reflects the cost of labor across several geographic markets, and we pay differently based on those defined markets. Base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The pay range for this position in Toronto, Ontario, Canada is C$154,000.00 - C$192,000.00 annually. Pay within this range varies by work location and may also depend on your qualifications, job-related knowledge, skills, and experience. Your recruiter can share more about the specific salary range for the job location during the hiring process. We also offer a comprehensive package of benefits including paid time off, 12 paid holidays per year, medical/dental/vision insurance, basic life insurance, and 401(k) to eligible employees.
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