DataJobs.io
← Back to all jobs

Job Description

The IT Controls Data Engineer will build and maintain the data infrastructure that powers audit readiness, IT controls, evidence automation, and continuous control monitoring. The role is based onsite in San Francisco, CA, and involves close collaboration with Security, IT, Infrastructure, Engineering, Risk Management, and auditors to translate complex system behavior into reliable control data.

Responsibilities

  • Develop and maintain robust data pipelines, datasets, and models to support IT controls data, covering access, identity, configuration, changes, ticketing, exceptions, and evidence data.
  • Implement data quality, lineage, reconciliation, and completeness checks to ensure control data is defensible for SOX and other audit use cases.
  • Design automated evidence generation workflows that yield complete, accurate, and repeatable audit populations, exports, dashboards, and control artifacts.
  • Build control 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 understand 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

  • Strong experience in data engineering, analytics engineering, or software/data systems, including building reliable datasets, pipelines, queries, dashboards, or automated reporting workflows.
  • Hands-on SQL proficiency and expertise with at least one scripting or programming language such as Python.
  • Experience working with enterprise system data, including identity platforms, HR systems, ticketing systems, cloud environments, source control systems, SaaS applications, or audit/compliance tooling.
  • Solid 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.
  • Capacity 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.

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 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, including accurate inventories, access populations, change records, configuration state, exception signals, and evidence generated directly from source systems.

Our objective is 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 construct the data infrastructure that underpins audit readiness, IT controls, evidence automation, and continuous control monitoring.

You will design and maintain pipelines, datasets, models, validation logic, dashboards, and evidence exports that render IT controls measurable, repeatable, and defensible.

Collaborating across Security, IT, Infrastructure, Engineering, Finance Risk Management, and auditors, you will translate complex system behavior into reliable control data products.

This is a technical builder role. The ideal candidate blends strong data engineering and analytics engineering skills with experience handling enterprise and security data, and can clearly articulate data lineage, source-system behavior, and control logic to technical and audit stakeholders.

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 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 strengthens control reliability.
  • You collaborate effectively with engineers without hindering delivery, while maintaining strong control standards.

About OpenAI

OpenAI is an AI research and deployment organization dedicated to ensuring that general purpose artificial intelligence benefits humanity. We push the boundaries of AI capabilities and strive to deploy them safely through our products. We value diverse perspectives and experiences as essential to responsibly advancing AI.

We are an equal opportunity employer and do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other protected characteristics. Background checks are conducted in accordance with applicable law, including fair chance ordinances where applicable. We provide reasonable accommodations to applicants with disabilities.

Compensation

Salary range: USD 293,000 to 385,000 per year. This position may include equity offers.

Similar Jobs

Get Job Alerts

New jobs delivered to your inbox.