Automating Data Platform Governance with Infrastructure as Code
Onboarding users, granting access, and integrating external data providers all required manual intervention. Permissions were handled through repeated administrative work, while vendor integrations depended on configuration that could vary from one implementation to the next.
As demand on the platform grew, that operating model became harder to sustain. Platform engineers were spending increasing time processing access and onboarding work instead of improving the platform itself.
The problem was not simply that individual requests took too long. Governance had been implemented as an operational process rather than as a repeatable capability of the platform.
Manual governance made the platform team a control point for every request
The existing model created several forms of operational risk.
Access configuration could vary across environments. Permissions were more difficult to manage consistently. User and vendor onboarding depended on platform-team availability. Each new integration created another opportunity for one-off configuration.
That model also made scale expensive. Growth in users, teams, and external providers increased the amount of administrative work required from the same engineering function responsible for evolving the platform.
The organization needed to preserve centralized governance without requiring engineers to execute every governance task manually.
Identity became the foundation for consistent access control
Factored began by restructuring Entra ID groups around a centralized identity-governance model.
The objective was to establish a consistent access-control foundation that other platform workflows could reference. Instead of treating permissions as isolated configuration decisions, access could be tied to defined identity groups and governed through a common structure.
This mattered because automation alone would not solve the underlying problem. Automating inconsistent permission logic would simply reproduce inconsistency faster. The access model first needed a standard representation that the platform could apply predictably.
Terraform moved platform configuration into repeatable workflows
Factored then implemented Infrastructure as Code using Terraform and configuration-driven workflows.
Platform resources and permissions that had previously required manual administration could be represented through standardized definitions and provisioned through repeatable workflows.
That changed the role of the platform team. Engineers no longer needed to execute every routine configuration directly. Instead, they could define the rules and reusable patterns through which approved infrastructure and access changes were applied.
Infrastructure as Code also created a clearer path for reviewing how platform configuration changed over time. The extent to which this improved auditability or reduced configuration drift should be confirmed against the client’s implementation and operating process before publication.
Reusable connector patterns reduced one-off vendor configuration
External data-provider onboarding presented a related problem.
When each vendor required a separate implementation path, the platform accumulated variation and additional maintenance overhead. Factored developed reusable connector templates intended to standardize the recurring parts of that work.
New integrations could then follow an established pattern rather than beginning with a custom configuration every time.
The value of that standardization was not simply faster implementation. It reduced the number of platform decisions that engineers had to recreate for each onboarding request while preserving a defined process for introducing external connections.
Approval and access lifecycle logic moved into the workflow
The final step was to incorporate approval processes and access lifecycle management into the automated operating model.
Where the workflow allowed it, approved requests could move through standardized provisioning without requiring the platform team to perform each underlying change manually.
This is the important distinction between automation and effective self-service. Self-service does not mean removing governance. It means allowing authorized users or systems to initiate predefined workflows while identity, policy, approvals, and infrastructure rules continue to constrain what can be provisioned.
For this organization, the goal was to make governance part of the mechanism by which the platform operated rather than a separate set of administrative tasks performed after a request arrived.
Governance became less dependent on manual platform administration
The new model reduced the platform team’s dependence on repetitive access and onboarding work.
Standardized provisioning gave users and external providers a more consistent path onto the platform. Reusable configuration patterns reduced the need to recreate common infrastructure decisions. Identity-driven controls provided a common basis for managing access.
The organization could therefore support additional platform demand without treating every new request as a new administrative workflow.
The available source material supports these outcomes qualitatively. Any claim about the exact reduction in engineering effort, onboarding time, configuration drift, security risk, or administrative workload should be added only if Engineering can provide approved evidence.
The broader lesson: governance scales when policy becomes platform logic
Data-platform governance becomes difficult to scale when policy is enforced primarily through tickets, manual configuration, and individual engineering intervention.
Infrastructure as Code provides a different operating model. Access rules, infrastructure definitions, and approved configuration patterns can be expressed in systems that apply them consistently and repeatably.
That does not remove the need for governance teams or engineering judgment. It changes where that judgment is exercised. Engineers define the controls, boundaries, and reusable patterns instead of repeatedly carrying out the same administrative actions.
For enterprise data platforms, that distinction is consequential. As the number of users, data products, and external integrations grows, governance needs to scale as part of the platform architecture rather than as a parallel manual process.
Factored’s work with this organization applied that principle across identity, infrastructure provisioning, external integrations, and access workflows: standardize the policy, encode the repeatable parts, and reserve engineering intervention for decisions that actually require engineering judgment.
