Skip to content
OpenAIOpenAI

IT Controls Data Engineer

As an IT Controls Data Engineer, you will build and maintain data infrastructure for audit readiness, IT controls, and continuous control monitoring. This role involves designing pipelines, datasets, and automated validation to ensure reliable control data.

About the job

About the Role

We are looking for an IT Controls Data Engineer to build the data infrastructure that powers audit readiness, IT controls, evidence automation, and continuous control monitoring.

In this role, 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 work across Security, IT, Infrastructure, Engineering, Finance Risk Management, and auditors to turn complex system behavior into reliable control data products.

This is a technical builder role. The ideal candidate is strong in data engineering and analytics engineering, comfortable working with enterprise and security system data, and able to explain data lineage, source-system behavior, and control logic clearly to technical and audit stakeholders.

You’ll be responsible for

  • 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.

We’re looking for someone with

  • 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.

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 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.

Skills

SQL, Python, Data Modeling, Data Pipelines, Cloud Infrastructure, Azure, AWS, GCP, Databricks, Salesforce

Fluidstack

Fluidstack

Austin, TX
Data Engineer
$269k+/yrOn-site5+ YOEData Engineering

Build and own production data pipelines, knowledge graph data models, and structured datasets from messy sources (PDFs, spreadsheets, telemetry) to power internal tools, dashboards, and ML models at a frontier AI compute infrastructure company. Requires experience operating depended-on pipelines, schema modeling, data quality engineering, and unstructured data extraction.

Anthropic

Anthropic

San Francisco, CA
Data Engineer, GTM
$320k+/yrHybrid5+ YOEData Engineering

Build and govern quote-to-cash data models and products integrating Salesforce, CPQ, billing, and finance systems. The role requires 5+ years of data engineering experience, strong SQL and Python skills, and expertise in self-service analytics for GTM teams.

Anthropic

Anthropic

San Francisco, CA
Infrastructure Capacity Planner, Demand Planning
$320k+/yrHybridData Engineering

Own medium-range demand forecasts for Anthropic's expanding infrastructure fleet across accelerators, CPU, storage, network, and managed services. The role requires hands-on SQL/Python modeling, large-scale infrastructure planning experience, and partnership with sourcing, Finance, and efficiency teams.

Thinking Machines Lab

Thinking Machines Lab

San Francisco, CA

Data Operations
$250k+/yrHybridData Engineering

Own end-to-end data sourcing and vendor operations that help researchers train and evaluate frontier AI models. The role requires strong judgment, communication, problem-solving, and comfort managing ambiguous, fast-changing projects.

OpenAI

OpenAI

Mountain View, CA
Data Engineer, Monetization Data Platform
$230k+/yrOn-siteData Engineering

Build and operate scalable monetization data platforms, pipelines, models, and quality systems spanning product, financial, and operational data. The role partners with Product Engineering, Finance, Accounting, Analytics, and GTM teams to deliver reliable, observable data products.