Description
Compensation
The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The salary range for this role is $459K – $536K, with generous equity, performance-related bonuses for eligible employees, and the following benefits.
Benefits include:
- Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts
- Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)
- 401(k) retirement plan with employer match
- Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)
- Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees
- 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time
- Mental health and wellness support
- Employer-paid basic life and disability coverage
- Annual learning and development stipend to fuel your professional growth
- Daily meals in our offices, and meal delivery credits as eligible
- Relocation support for eligible employees
- Additional taxable fringe benefits, such as charitable donation matching and wellness stipends
About the Team
The Applied organisation 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 behaviour to trustworthy subscriber, payment, and revenue measurement.
Responsibilities
- 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 behaviour, 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.
Requirements
- 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.
Success Metrics
- 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.