The onsite position in San Francisco, CA focuses on building and maintaining the data infrastructure that powers audit readiness, IT controls, evidence automation, and continuous control monitoring. The role involves designing pipelines, datasets, models, validation logic, dashboards, and exports while collaborating with Security, IT, Infrastructure, Engineering, Risk Management, and auditors.
Responsibilities
- Develop and maintain dependable data pipelines, models, and datasets to support IT controls across areas such as access management, identity, configuration, change history, ticketing, exceptions, and evidence capture.
- Implement data quality, lineage tracking, reconciliation, and completeness checks to ensure control data is defensible for SOX and other audit needs.
- Design automated workflows that generate comprehensive, accurate, and repeatable audit populations, exports, dashboards, and control artifacts.
- Craft monitoring logic to detect drift, missing evidence, stale access, direct system changes, overdue activity, and other control exceptions.
- Collaborate with Security, IT, Infrastructure, Engineering, Risk Management, and system owners to map source systems, validate data, and improve automation reliability.
- Translate technical system behavior, data flows, access models, and validation results into clear explanations for auditors, control owners, and technical stakeholders.
Requirements
- Experience in data engineering, analytics engineering, or related software/data systems roles, with a track record of building reliable datasets, pipelines, queries, dashboards, or automated reporting workflows.
- Hands-on SQL proficiency and competence in at least one scripting or programming language such as Python.
- Experience working with enterprise system data, including identity platforms, HR systems, ticketing tools, cloud environments, source control systems, SaaS applications, or audit and compliance tooling.
- Strong understanding of data modeling, lineage, completeness, accuracy, reconciliation, validation, observability, and repeatability.
- Ability to navigate 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.
- Demonstrated ownership, good judgment, and meticulous attention to detail in high-stakes, time-sensitive contexts.
Technologies
- SQL
- Python
- Entra ID
- Workday
- GitHub
- Databricks
- Salesforce
- Azure
- AWS
- GCP
About the Team
The IT and Security organization builds the systems, data foundations, and automation that enable OpenAI to operate securely and reliably at scale. Its remit spans identity, access, infrastructure security, enterprise systems, and internal productivity. As the company grows, audit readiness and control assurance increasingly depend on accurate inventories, access populations, change records, configuration state, exception signals, and evidence generated directly from source systems. The team aims to move beyond manual evidence collection by delivering scalable data products, automated validation, and continuous control monitoring that render security and IT controls measurable, repeatable, and defensible.
About the Role
We are seeking an IT Controls Data Engineer to build the data infrastructure that underpins audit readiness, IT controls, evidence automation, and continuous control monitoring. You will design and maintain the pipelines, datasets, models, validation logic, dashboards, and evidence exports that make IT controls measurable, repeatable, and defensible. You will collaborate with Security, IT, Infrastructure, Engineering, Finance Risk Management, and auditors to translate complex system behavior into reliable control data products. This is a technical builder role. The ideal candidate excels in data and analytics engineering, is comfortable with enterprise and security data, and can clearly articulate data lineage, source-system behavior, and control logic to both technical and audit audiences.
Nice to Have
- Experience with Entra ID, Workday, GitHub, Databricks, Salesforce, or similar platforms.
- Experience with cloud infrastructure environments such as Azure, AWS, or GCP.
You Might Thrive In This Role If
- You enjoy turning messy operational processes into clean, repeatable systems.
- You operate at the intersection of data, controls, engineering, and audit.
- You can dive deep technically while also explaining your work 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 strengthens control reliability.
- You collaborate with engineers without slowing them down, while upholding strong control standards.
About OpenAI
OpenAI is an AI research and deployment organization committed to ensuring that artificial intelligence benefits all of humanity. We push the boundaries of AI capabilities and pursue safe deployment worldwide. We value safety, human-centered design, and diverse perspectives in shaping the future of technology. OpenAI is an equal opportunity employer and does not discriminate based on race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, or other protected characteristics. We provide reasonable accommodations to applicants with disabilities and comply with applicable equal employment opportunity policies and privacy practices.
Compensation
Annual base salary range: USD 293,000 – 385,000, with equity opportunities offered as part of compensation.
