Role overview
- 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.
- 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.
- Ability to reason through messy source-system data, inconsistent identifiers, nested groups, stale records, missing owners, direct assignments, and downstream application drift.
- Experience supporting security, IT controls, SOX, audit readiness, risk, compliance, or regulated technology environments.
- Ability to explain technical systems, data flows, and control logic clearly to both engineering and audit stakeholders.
- Strong ownership, judgment, and attention to detail in high-stakes, time-sensitive environments.
Preferred qualifications
- Experience with Entra ID, Workday, GitHub, Databricks, Salesforce, or similar platforms.
- Experience with cloud infrastructure environments such as Azure, AWS, or GCP.
- You like turning messy operational processes into clean, repeatable systems.
- You enjoy working at the intersection of data, controls, engineering, and audit.
- You can go deep technically, but also explain your work clearly to auditors and executives.
- You care about evidence quality, data integrity, and defensible documentation.
- You are energized by building automation that reduces manual effort and improves control reliability.
- You can partner with engineers without slowing them down, while still maintaining a strong control standard.
About the company
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.
As OpenAI grows, audit readiness and control assurance increasingly depend on reliable data: accurate system inventories, access populations, change records, configuration state, exception signals, and evidence generated directly from source systems. Our goal is to move beyond manual evidence collection and build scalable data products, automated validation, and continuous control monitoring that make security and IT controls measurable, repeatable, and defensible.
Tags & focus areas
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