Valon Tech
About the Company
Valon is building the AI-native operating system for regulated finance, starting with mortgage servicing.
We're a Series C company backed by a16z, transforming industries that others have written off as too complex to innovate.
Rather than build on top of broken legacy systems, we took a different approach: we built and operate our own mortgage servicing business managing $110+ billion in loans. This wasn't the end goal, it was how we deeply understood the complexity needed to build software that actually works in regulated industries.
The results speak for themselves. We've transformed mortgage servicing from a 0% margin business into 60%+ margins while dramatically improving customer experience. Major enterprise contracts are now deploying across the industry.
ValonOS is our unified platform that makes every process structured and programmable and it is perfectly positioned for the AI era. When everything flows through one system with rich data, AI agents don't just automate tasks, they continuously improve entire operations. Mortgage servicing is just the beginning of our vision to transform regulated industries and beyond.
About the Role We’re looking for a Senior Data Engineer to build and own the data systems that power the next phase of Valon’s platform — the AI-native operating system for regulated finance.
This is a foundational, multi-year initiative to make ValonOS structured, inspectable, and programmable — the bedrock that enables AI to operate safely and effectively in real-world financial systems. You’ll architect the pipelines, orchestration, and frameworks that transform Valon’s data infrastructure into a product: reliable, observable, and built for scale.
This role goes far beyond traditional “data plumbing.” It’s about engineering data as a system, not a service — ensuring every team at Valon can move with precision and speed through a robust, scalable data foundation. You’ll collaborate with data analysts, forward-deployed engineers, and product teams to design infrastructure that’s production-grade, auditable, and AI-ready.
You’ll think in systems and tradeoffs, design for scale and observability, and bring a product mindset to everything from orchestration to modeling frameworks. Some example problems on the roadmap:
Migrate dbt Cloud jobs to Airflow for reliability, flexibility, and cost optimization.
Stand up a medallion architecture for analytics and reporting.
Implement data contracts and observability frameworks (e.g., Great Expectations).
Build self-serve data tooling that allows every team to access high-quality data safely and efficiently.
Lay the groundwork for 10x scaling of multi-tenant SaaS data operations.
This is a high-impact role for someone who thrives on complexity and wants to shape the data foundation that makes regulated AI possible.
Responsibilities
Design, build, and evolve Valon’s core data infrastructure — orchestration, modeling frameworks, and data pipelines.
Partner with analytics, engineering, and product teams to define and implement data contracts and observability systems.
Develop fault-tolerant, auditable, and high-performance pipelines for both internal and client-facing data applications.
Migrate and modernize existing systems (e.g., dbt Cloud → Airflow) to support scale and cost efficiency.
Implement the medallion architecture to structure analytics layers and ensure reliability at scale.
Build and maintain self-serve data access tools to empower internal teams.
Own technical strategy and execution for Valon’s data foundation — balancing near-term performance needs with long-term scalability.
Advocate for best practices in data modeling, reliability, observability, and developer experience across the company.
Ideal Background
5+ years of data engineering or systems engineering experience , ideally in startup or growth-stage environments (Series B–E).
Proven experience designing and scaling data infrastructure — from ingestion and orchestration to modeling and observability.
Deep understanding of modern data stacks: Python, SQL, dbt, Airflow, and cloud-native environments (AWS/GCP/Azure).
Strong grasp of data architecture patterns (e.g., medallion, lakehouse, modular data modeling).
Experience implementing data quality frameworks, observability tools, or data contracts at scale.
A
product mindset
— you care about usability, reliability, and the developer experience of your data systems.
Bonus: Experience in
fintech, logistics, or other regulated, data-heavy domains .
Benefits
Compensation: Competitive salary with a meaningful stake in the company via equity, and 401k plan.
Health & well-being: We’ll invest in your physical and mental well-being with comprehensive medical, dental, & vision benefits.
Commuter benefits: We offer pre-tax deductions for public transportation, rideshare services, and parking expenses to make your commute more affordable and convenient.
Grow together: Company wide orientation for you to successfully onboard and other learning & development opportunities including regular review cycles that feature 360 degree feedback.
Play together: Quarterly budgets for team and company outings. Use it for team swag, cooking classes, or team dinners!
Generous time off: Flexible paid time off, sick days, and 11 company holidays.
Baby bonding time!: 12 weeks off for both birthing and non-birthing parents - fully paid so you can focus your energy on your newest addition.
Throughout the interview process, please remember that emails will only be from valon.com emails. We won't ever be asking for any personally identifiable information during the interview process itself. Please reach out to talent@valon.com if you have any requests to verify the authenticity of an outreach.
Valon is an equal opportunity employer that is committed to diversity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, or local laws. Valon makes hiring decisions based solely on qualifications, merit, and business needs at the time.
#J-18808-Ljbffr
We're a Series C company backed by a16z, transforming industries that others have written off as too complex to innovate.
Rather than build on top of broken legacy systems, we took a different approach: we built and operate our own mortgage servicing business managing $110+ billion in loans. This wasn't the end goal, it was how we deeply understood the complexity needed to build software that actually works in regulated industries.
The results speak for themselves. We've transformed mortgage servicing from a 0% margin business into 60%+ margins while dramatically improving customer experience. Major enterprise contracts are now deploying across the industry.
ValonOS is our unified platform that makes every process structured and programmable and it is perfectly positioned for the AI era. When everything flows through one system with rich data, AI agents don't just automate tasks, they continuously improve entire operations. Mortgage servicing is just the beginning of our vision to transform regulated industries and beyond.
About the Role We’re looking for a Senior Data Engineer to build and own the data systems that power the next phase of Valon’s platform — the AI-native operating system for regulated finance.
This is a foundational, multi-year initiative to make ValonOS structured, inspectable, and programmable — the bedrock that enables AI to operate safely and effectively in real-world financial systems. You’ll architect the pipelines, orchestration, and frameworks that transform Valon’s data infrastructure into a product: reliable, observable, and built for scale.
This role goes far beyond traditional “data plumbing.” It’s about engineering data as a system, not a service — ensuring every team at Valon can move with precision and speed through a robust, scalable data foundation. You’ll collaborate with data analysts, forward-deployed engineers, and product teams to design infrastructure that’s production-grade, auditable, and AI-ready.
You’ll think in systems and tradeoffs, design for scale and observability, and bring a product mindset to everything from orchestration to modeling frameworks. Some example problems on the roadmap:
Migrate dbt Cloud jobs to Airflow for reliability, flexibility, and cost optimization.
Stand up a medallion architecture for analytics and reporting.
Implement data contracts and observability frameworks (e.g., Great Expectations).
Build self-serve data tooling that allows every team to access high-quality data safely and efficiently.
Lay the groundwork for 10x scaling of multi-tenant SaaS data operations.
This is a high-impact role for someone who thrives on complexity and wants to shape the data foundation that makes regulated AI possible.
Responsibilities
Design, build, and evolve Valon’s core data infrastructure — orchestration, modeling frameworks, and data pipelines.
Partner with analytics, engineering, and product teams to define and implement data contracts and observability systems.
Develop fault-tolerant, auditable, and high-performance pipelines for both internal and client-facing data applications.
Migrate and modernize existing systems (e.g., dbt Cloud → Airflow) to support scale and cost efficiency.
Implement the medallion architecture to structure analytics layers and ensure reliability at scale.
Build and maintain self-serve data access tools to empower internal teams.
Own technical strategy and execution for Valon’s data foundation — balancing near-term performance needs with long-term scalability.
Advocate for best practices in data modeling, reliability, observability, and developer experience across the company.
Ideal Background
5+ years of data engineering or systems engineering experience , ideally in startup or growth-stage environments (Series B–E).
Proven experience designing and scaling data infrastructure — from ingestion and orchestration to modeling and observability.
Deep understanding of modern data stacks: Python, SQL, dbt, Airflow, and cloud-native environments (AWS/GCP/Azure).
Strong grasp of data architecture patterns (e.g., medallion, lakehouse, modular data modeling).
Experience implementing data quality frameworks, observability tools, or data contracts at scale.
A
product mindset
— you care about usability, reliability, and the developer experience of your data systems.
Bonus: Experience in
fintech, logistics, or other regulated, data-heavy domains .
Benefits
Compensation: Competitive salary with a meaningful stake in the company via equity, and 401k plan.
Health & well-being: We’ll invest in your physical and mental well-being with comprehensive medical, dental, & vision benefits.
Commuter benefits: We offer pre-tax deductions for public transportation, rideshare services, and parking expenses to make your commute more affordable and convenient.
Grow together: Company wide orientation for you to successfully onboard and other learning & development opportunities including regular review cycles that feature 360 degree feedback.
Play together: Quarterly budgets for team and company outings. Use it for team swag, cooking classes, or team dinners!
Generous time off: Flexible paid time off, sick days, and 11 company holidays.
Baby bonding time!: 12 weeks off for both birthing and non-birthing parents - fully paid so you can focus your energy on your newest addition.
Throughout the interview process, please remember that emails will only be from valon.com emails. We won't ever be asking for any personally identifiable information during the interview process itself. Please reach out to talent@valon.com if you have any requests to verify the authenticity of an outreach.
Valon is an equal opportunity employer that is committed to diversity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, or local laws. Valon makes hiring decisions based solely on qualifications, merit, and business needs at the time.
#J-18808-Ljbffr