Staff Data Engineer - Federal (Auth0)
Okta, Inc. - Bellevue, Washington; Chicago, Illinois; New York, New York; Washington, DC
Posted May 1, 2026
Benefits
- Parental leave
- Not verified
- Non-birth-parent leave
- Not verified
- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
- Not verified
- Relocation assistance
- Not verified
- Childcare support
- Not verified
- Learning budget
- Not verified
- Verification
- Not verified
- Salary
- Not verified not verified - source not recorded; timestamp not recorded
- 401(k) match
- Not verified
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Market context
- Median wage (BLS OEWS)
- $111,944 national median
- Projected growth (BLS Employment Projections)
- +13.7% - Much faster than average
84% above the BLS national median for data and ml aggregate.
Matched to SOC 15-1252 - Data and ML aggregate by role bucket.
Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.
Schedule
- Shift type
- Not verified
- Weekend work
- Not verified
Application
- Cover letter
- Not verified
- Assessment
- Not verified
- Deadline
- Not stated
Where they hire
State eligibility is not yet verified.
About this role
Staff Data Engineer - Federal (Auth0) Bellevue, Washington; Chicago, Illinois; New York, New York; Washington, DC Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. The Auth0 Data Engineering Team Within Auth0, the Data Engineering team builds solutions to support analytics needs for the whole organization and is in charge of the Data Platform. It is divided into 3 groups: - Pipeline team , sitting closer to the Platform team and data producers and in charge of the efficient data ingestion and provision of quick access to unmodeled data - Warehouse team sitting closer to the business teams and data consumers and in charge of modeling the data in the data warehouse to abstract away the complexity for data consumers, simplifying the organization's analysis, reporting and decision-making - Interface team responsible for creating and managing connections between the data platform and various external systems (internal or external facing), making sure everyone has access to consistent and reliable data The Staff Data Engineer Opportunity Reporting to the manager of the Data Engineering Pipeline team, the
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