Data Engineering Manager, Growth & Revenue
openai
Job Score
100 ptsAbout the Team
The Applied organization brings OpenAI’s most advanced technology to the world through products like ChatGPT and the APIs that power a growing ecosystem of developer and enterprise applications. Data Engineering builds and operates the trustworthy, secure, and reliable data systems that power decisions across OpenAI.
About the Role
We’re looking for a Data Engineering Manager to lead the Growth & Revenue data engineering team. This leader will own the data strategy and execution for the data subject areas spanning growth accounting across all product surfaces, product partnerships, checkout, billing, payments, revenue, and monetization, helping OpenAI understand how people adopt, engage with, and pay for our products. You will partner closely with several Data Science, Business, and Engineering partners to connect product behavior to trustworthy subscriber, payment, and revenue measurement.
In this role, you will:
Build, manage, and grow a high-performing, inclusive team across the Growth & Revenue data subject areas.
Define the data strategy for all the data subject areas you own.
Deliver durable, well-modeled data products that connect product behavior, subscription state, checkout events, payment outcomes, and revenue.
Establish trusted metric definitions and data quality standards so product, growth, finance, and executive leaders can make fast, consistent decisions.
Partner with Data Science and Product teams to support experimentation, causal measurement, funnel analysis, and scalable self-serve analytics.
Partner with Finance and Financial Engineering to ensure analytical revenue views reconcile to financial truth and production billing systems.
Raise operational excellence for critical pipelines, including reliability, observability, privacy, governance, and incident response.
Set a clear roadmap, make principled tradeoffs, and communicate progress and risk across technical and business stakeholders.
You might thrive in this role if you:
Have deep experience leading and scaling data engineering teams in a fast-moving product or technology environment.
Bring strong technical judgment across modern data systems, including SQL, Python or Scala, Spark, orchestration, dimensional and event modeling, and lakehouse or warehouse architectures.
Have built trusted growth, lifecycle, attribution, subscription, billing, payments, revenue, or monetization data products at meaningful scale.
Can turn ambiguous business questions into durable data contracts, metric definitions, and technical roadmaps.
Build unusually strong partnerships with Data Science, Product, Finance, Financial Engineering, GTM, and Engineering.
Care deeply about data quality, privacy, security, and the operational health of systems used for consequential decisions.
Are an excellent people leader: you hire well, develop talent, give clear feedback, and create an environment where diverse perspectives do their best work.
What success looks like
In the first 90 days, you have earned trust with the team and partners, clarified ownership boundaries, assessed the current data portfolio, and aligned on a prioritized roadmap.
Within a year, Growth & Revenue stakeholders rely on a smaller set of trustworthy, well-owned datasets and metrics for lifecycle, attribution, subscriber, billing, payment, monetization, and revenue decisions.
The team operates with clear goals, healthy execution rhythms, strong reliability standards, and a hiring and development plan that matches the domain’s ambition.
This role is based in our San Francisco headquarters. We offer relocation assistance for new employees.
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.
To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.
OpenAI Global Applicant Privacy Policy
At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
About Data
The Data field has undergone a radical transformation with the rise of Generative AI. Data professionals are fundamental for evidence-based decision-making across all industries.
Key specializations include Data Engineering, Data Science, Business Intelligence, Machine Learning Engineering, and Analytics. Tools like SQL, Python, Spark, dbt, and cloud platforms (AWS, GCP, Azure) are essential.
The data market continues with high demand and salaries among the most competitive in the technology sector, with many remote work opportunities.
About Engineering
Software Engineering goes beyond traditional development, focusing on scalability, performance, and system architecture. Software engineers are responsible for designing infrastructures that support millions of simultaneous users.
Skills include microservices architecture, DevOps, cloud computing, application security, and performance optimization. Knowledge of containerization (Docker, Kubernetes) and CI/CD is increasingly required.
Senior software engineers are rare and highly compensated professionals, with opportunities at major global tech companies.
About Business Intelligence
Business Intelligence (BI) is the area responsible for transforming raw data into strategic information for decision-making. BI professionals build dashboards, reports, and analyses that help companies understand their performance and identify growth opportunities.
Key skills include data modeling (star schema, snowflake), ETL (extraction, transformation, loading), advanced SQL, BI tools (Power BI, Tableau, Looker), data warehousing, KPIs, and business metrics analysis (MRR, churn, cohort). Knowledge of dbt, Airflow, and data pipelines is a differentiator.
BI professionals in technology companies are highly valued, especially those who master data visualization, analytics engineering, and can translate complex data into actionable insights for the business. The field offers opportunities from BI analyst to head of data, with a focus on data-driven decision making.
Discover Other Areas
Understand the scope of work, key skills, and tools used in different career areas.
About Technical Support
Technical Support is essential to ensure customer satisfaction and retention. Support professionals resolve technical issues, document solutions, and identify patterns that can lead to product improvements.
Key skills include troubleshooting, customer service, technical documentation, ITIL knowledge, and ticketing tools (Zendesk, Freshdesk, Intercom).
Technical support has evolved from a reactive to a proactive function, with high-level professionals working in Customer Engineering and Support Engineering.
About Copywriting
The Copywriting area is responsible for creating persuasive, creative, and strategic texts for various communication channels. Copywriting professionals transform ideas into words that engage, convert, and build brand voice.
Key skills include advertising copywriting, script writing for videos and podcasts, persuasive writing, tone of voice, and editorial guidelines. Knowledge of SEO writing, Grammarly, and text productivity tools is a differentiator.
Copywriting professionals in technology companies are highly valued, especially those who master copy for landing pages, email sequences, and funnel content. The field offers opportunities from junior copywriter to head of copy, with a focus on creativity, persuasion, and performance.
About Project Management
Project Management is essential to ensure strategic initiatives are delivered on time, within scope, and with quality. PM professionals coordinate teams, manage risks, and communicate with stakeholders.
Key methodologies include PMBOK, PRINCE2, Scrum, and Kanban. Tools like Jira, Asana, Monday, and MS Project are widely used in daily work.
Certifications like PMP and PgMP are important differentiators in the market, with growing demand in technology and consulting companies.
About Information Security
The Information Security area is one of the most strategic and in-demand fields in the technology market. With the rise of cyberattacks, data breaches, and regulations like LGPD and GDPR, companies of all sizes invest heavily in professionals who can protect their digital assets.
Key specializations include Network Security, Cloud Security (AWS, Azure, GCP), Offensive Security (Penetration Testing, Red Team), Defensive Security (SOC, Blue Team), AppSec, and Security Governance. Tools like SIEM (Splunk, QRadar), firewalls, EDR, and Vulnerability Management platforms are essential.
Certifications like CISSP, CEH, OSCP, CompTIA Security+, and AWS Security Specialty are important differentiators. Information security professionals are among the highest-paid in the sector, with growing demand especially in fintechs, healthtechs, and large enterprises.
About Communications
The Communications area is strategic for building and maintaining a company's institutional image. It encompasses corporate, internal, and external communication, public relations, press office, and reputation management. Communications professionals are responsible for delivering consistent messages that strengthen the employer brand and market positioning.
Key skills include strategic writing, communication planning, crisis management, media relations, corporate content production, event organization, and digital communication. Knowledge of communication CRMs, press release distribution platforms, and media monitoring tools (Meltwater, Cision) is a differentiator.
Corporate communicators in technology companies are highly valued, especially those who master change communication, employee engagement, and digital communication. The field offers opportunities in startups, scale-ups, and large corporations, with a focus on storytelling, organizational culture, and innovation communication.
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