The opportunity
The IT and Security organization builds the systems, data foundations, and automation that help OpenAI operate securely and reliably at scale. We support critical domains across identity, access, infrastructure security, enterprise systems, and internal productivity.
What you'll do
Building reliable data pipelines, models, and datasets for IT controls,: including access, identity, configuration, change, ticketing, exception, and evidence data.
Creating data quality, lineage, reconciliation, and completeness checks that: make control data defensible for SOX and other audit use cases.
Designing automated evidence generation workflows that produce complete,: accurate, and repeatable audit populations, exports, dashboards, and control artifacts.
Developing control monitoring logic to detect drift, missing evidence, stale: access, direct system changes, overdue activity, and other control exceptions.
Partnering with Security, IT, Infrastructure, Engineering, Risk Management,: and system owners to understand source systems, validate data, and improve automation reliability.
Translating technical system behavior, data flows, access models, and: validation results into clear explanations for auditors, control owners, and technical stakeholders.
What they're looking for
- Strong data engineering, analytics engineering, or software/data systems: experience, including building reliable datasets, pipelines, queries, dashboards, or automated reporting workflows.
- Hands-on SQL experience and proficiency with at least one scripting or programming language such as Python.
- Experience working with enterprise system data, such as identity platforms,: HR systems, ticketing systems, cloud environments, source control systems, SaaS applications, or audit/compliance tooling.
- Strong understanding of data modeling, lineage, completeness, accuracy,: reconciliation, validation, observability, and repeatability.
