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OpenAI

Data Engineering Manager, Growth & Revenue

San FranciscoUnited States
Manager · FullTime · Applied AI
POSTED 14 SEPTVERIFIED 25M AGO
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Role
61 days opentrue age
Past the 40d median close
Posted 14 Sept · n=121
Payats field
$459k–536kposted
▲ +71% vs market median $290k
$241k$536k
Market p25–p75
$241k–$404k
OpenAI p25–p75
$340k–$434kn=3
H-1B median · Data engineering
$250k
SF Bay Area · n=8 · 365d to 11 Nov
CompanyOpenAI →
840open roles
Opened · 30d
+129
Closed · 30d
−87
Signal
● Steady+42 net
14d of snapshots · 30d window
Market
148open · Manager Data engineering
Opened · 7d
+1711% of open
All data engineering
3,825open
All tracked boards · live 15 Nov · n=148
Visa
210H-1B LCAs · FY26
Median wage
$260k
UK licensed sponsor
✓Worker (A rating)
LCAs FY26 · n=210 · to 2026-06-30
PythonScalaSparkSQL

About 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.

Source · OpenAIFirst seen 3 NovOriginal ↗