Why This Job is Featured on The SaaS Jobs
This Engineering Manager remit sits in a core SaaS pressure point: the billing and revenue data layer that underpins pricing, invoicing, renewals, and forecasting. Financial data quality becomes harder as products add plans, usage dimensions, and integrations, and this role is positioned at that intersection of monetization systems, data pipelines, and operational reporting. The emphasis on partnering with Finance and go to market functions signals work that directly affects how a SaaS business measures and runs its commercial engine.
For a SaaS career, the value is in learning how to treat data as an internal product with clear consumers, reliability targets, and governance. Leading a mixed team of software and data engineers builds fluency across platform engineering and analytics engineering, while the focus on observability and validation develops durable practices for metrics trust. Experience reducing vendor dependence and integrating multiple providers also maps well to common SaaS modernization and scale-up initiatives.
This role tends to suit managers who like cross-functional problem framing and can translate business definitions into technical contracts without losing rigor. It fits someone comfortable owning end-to-end outcomes across systems boundaries, and who enjoys building mechanisms that prevent recurring issues rather than reacting to them.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
About the Team
Within Applied Engineering, the Financial Engineering team ensures that our products are monetized effectively to accommodate customers' varying needs and scales. Collaborating closely with the GTM and Finance teams, we strive to tailor our billing stack to our evolving internal requirements.
About the Role
We’re looking for a Senior Engineering Manager to own Financial Data Quality. You’ll lead a team spanning Software Engineers and Data Engineers to ensure our financial data remains consistent, fresh, and accurate as we evolve our billing systems and integrate with additional vendors. We partner across Finance and go-to-market (GTM) functions to ensure financial data is accurate, consistent, and usable—especially as we evolve our systems architecture and scale.
What You’ll Do
Own financial data quality end-to-end (consistency, freshness, accuracy) across billing, revenue, and related financial data flows.
Drive the strategy and execution to bring systems and data capabilities in-house, reducing dependence on external vendors while maintaining operational rigor.
Partner with stakeholders across Finance and GTM to define data needs, deliver outputs in expected formats, and ensure data reliability as systems evolve.
Establish mechanisms for data quality monitoring, validation, and observability, so issues are detected quickly and trust in metrics remains high.
Ensure our data model and reporting outputs support both operational needs and finance workflows at scale.
You Might Thrive in This Role If You
Have managed teams that include software engineers who build/modify core systems as well as data-focused engineers—especially in domains where correctness matters.
Have a passion for data, think of data as a product itself, and can act as that product owner.
Are strong in SQL and data concepts, and can reason about data modeling, validation, lineage, and reliability.
Have experience with system migrations, reducing vendor dependency, or integrating multiple providers/sources into a consistent set of metrics.
Communicate effectively with Finance and GTM stakeholders, translating needs into technical plans and delivering outputs (ie. dashboards, curated tables, exports, APIs, etc.).
Care deeply about operational excellence: monitoring, incident response, and building resilient systems.
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
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