Closed listing
Finance Automation Lead
- Toronto, ON, Canada
This opening has closed.
The original listing is kept below for reference.
Job details
- Experience
- At least 3+ years of experience building data systems in a finance, analytics, or data engineering role
- Posting language
- English
- Posted
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Original job description
Archived listing. The details below describe a past opening.
Location
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 Role
As 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
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Design and deploy AI agents that automate data fetching, analysis, reporting, and forecasting workflows
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Architect data pipelines connecting financial planning systems (Adaptive) to Snowflake and downstream applications
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Build semantic layers that enable non-technical finance team members to access data through natural language
Create Finance Tools & Products
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Develop internal tools that transform manual finance processes into automated, scalable products
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Build dashboards and self-service interfaces that eliminate analyst bottlenecks
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Create systems that enable managers to answer their own headcount, budget, and forecast questions without finance intervention
Own Data Architecture for Finance
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Organize finance data for best-in-class LLM capabilities
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Design data models that support automated analysis, real-time querying, and AI agent interactions
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Establish data quality frameworks and governance for financial systems
Drive Automation at Scale
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Identify high-value automation opportunities across Finance (accruals, reporting, forecasting, variance analysis)
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Implement workflow automation using tools like Gumloop, Claude, and custom-built agents
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Measure and improve automation accuracy, reducing manual intervention over time
What You Will Bring
Technical Foundation
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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
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Advanced SQL proficiency with ability to design complex data models and optimize query performance
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Production experience with Python for data engineering, automation, and AI agent development
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Hands-on experience with modern data warehouses (Snowflake, BigQuery, or similar)
AI & Automation Expertise
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Deep understanding of LLM capabilities, limitations, and prompt engineering best practices
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Experience architecting semantic layers or natural language interfaces for data access
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Familiarity with AI orchestration frameworks (LangChain, LlamaIndex, or similar)
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Proven ability to identify high-ROI automation opportunities and implement end-to-end solutions
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Experience with workflow automation tools and API integrations
Data Architecture & Systems Design
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Strong data modeling skills with focus on enabling both human analysts and AI agents
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Experience designing data pipelines that connect planning systems (like Adaptive, Anaplan) to data warehouses
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Understanding of data governance, quality frameworks, and metadata management
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Ability to architect scalable systems that reduce analyst bottlenecks and enable self-service
Product & Business Mindset
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Builder mentality with ability to ship functional products, not just analyses
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Experience translating messy business problems into clean technical solutions
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Strong stakeholder management skills with ability to influence senior finance leadership
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Comfort working in ambiguous, fast-moving environments with evolving requirements
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Systems thinking approach to understanding complex problems and their root causes
Bonus points if you have:
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Experience in fintech, real estate tech, or high-velocity transaction businesses
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Background in financial planning & analysis (FP&A) or corporate finance
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Familiarity with finance-specific tools (Adaptive Insights, NetSuite, etc.)
Compensation
Our compensation plan consists of a base salary, Opendoor equity and a comprehensive package of benefits including paid time off, paid holidays, medical/dental/vision insurance, basic life insurance, and 401(k) to eligible employees. All compensation parameters are based on experience.
At Opendoor our mission is to tilt the world in favor of homeowners and those who aim to become one. Homeownership matters. It's how people build wealth, stability, and community. It's how families put down roots, how neighborhoods strengthen, how the future gets built. We're building the modern system of homeownership giving people the freedom to buy and sell on their own terms. We’ve built an end-to-end online experience that has already helped thousands of people and we’re just getting started.
More about this job
Responsibilities
As a Senior Finance Data Engineer, you will design and deploy AI agents to automate finance workflows and build tools that transform manual processes into scalable products. You will also own the data architecture for finance, ensuring data quality and enabling self-service capabilities.
Requirements
Candidates should have 3+ years of experience in data systems, advanced SQL proficiency, and production experience with Python. A deep understanding of LLM capabilities and experience with data governance and automation tools are also required.
Skills
- Data Engineering
- SQL
- Python
- AI Agents
- Data Pipelines
- Data Modeling
- Automation
- Data Governance
- Financial Systems
- Dashboard Development
- Stakeholder Management
- Natural Language Processing
- Workflow Automation
- Semantic Layers
- Data Quality
- Business Analysis
Remote locations
- Toronto
Remote locations (standardized)
- Toronto, Ontario, Canada
Visa sponsorship
Not detected in the job text
Hiring contact
President
Categories
- Technology
- Finance & Accounting
- Data & Analytics
Keywords
- Finance
- Data Engineer
- AI
- Data Architecture
- Automation
- SQL
- Python
- Data Pipelines
- Snowflake
- BigQuery
- LLMs
- Natural Language Processing
- Semantic Layers
- Workflow Automation
- Data Governance
- Financial Planning
- Dashboards
- Self-Service
- Data Quality
- Analytics