Data Governance & Security for Healthcare
HIPAA requires that only authorized staff see patient data and that access is logged. We classify PHI, apply row-level security and masking, and keep the audit trail.
Data Governance & Security
A compliance framework tells you what's missing. It doesn't write the row-level security policy, configure the encryption, or build the deletion pipeline. We engineer the access control, encryption, audit logging, and retention controls that a SOC 2 or HIPAA audit actually tests.
We work hands-on with: Vault, Okta, PostgreSQL, Snowflake, Terraform, Auth0, Kubernetes.
Engineering-first
we build the control, not just name it
Framework-mapped
SOC 2, HIPAA, PCI-DSS, GDPR
Engineering, not audit
we build the controls, not the report
Data governance and security engineering builds the row-level security, encryption, and audit logging that a compliance framework requires but doesn't build for you.
What Data Security Engineering & Governance Actually Involves
Data security engineering services and data governance consulting build the controls a compliance program requires: sensitive data discovery, data classification, access control at the database (row-level security, column masking), data encryption services and key management, and audit logging and retention pipelines. A compliance framework tells you a control is required. This is the engineering that makes it real, not just documented.
Most governance failures aren't technical. They're a tool bought and never operationalized. The catalog or policy platform works fine. What's missing is who owns wiring it into the actual database.
Discovery: Sensitive data gets classified once in a spreadsheet and never re-scanned as schemas change, so PII ends up in columns nobody flagged.
Access control: Permissions get granted ad hoc and rarely revoked, so "least privilege" stays a policy sentence, not a database grant.
Encryption & secrets: Static database passwords sit in an env file long after the KMS and Vault setup was budgeted for.
Audit & retention: Deletion requests clear the primary table but never reach the replica, the backup, or the cache.
45% of cloud databases are publicly accessible due to misconfiguration
Not a sophisticated attack. Nobody engineered the access control before the database went live.
The assessment we hand you names the exposure up front : where sensitive data actually lives, who can reach it today, what's encrypted, what's logged, and which specific control closes each gap against the framework you're working toward.
Problems That Trigger This Engagement
- A SOC 2, HIPAA, or PCI-DSS audit is on the calendar and controls are informal
- A customer security questionnaire cost you a deal, or nearly did
- You don't actually know who can access sensitive data in your own database
- A new privacy regulation now covers data you didn't previously have to protect
- You bought a governance or catalog tool and never finished configuring it
- Access requests get handled ad hoc, with no consistent policy behind them
Match Your Situation to the Fix
A quick lookup across the four parts of a governance and security engagement.
| Situation | Likely Solution |
|---|---|
| A SOC 2, HIPAA, or PCI-DSS audit is on the calendar and controls are informal | Audit Logging, Retention & Deletion Engineering — audit trails that answer who accessed what and when |
| A customer security questionnaire cost you a deal, or nearly did | Encryption & Secrets Overhaul — field-level encryption and KMS-backed key management |
| You don't actually know who can access sensitive data in your own database | Access Control Engineering — RBAC/ABAC redesigned around least privilege, enforced at the database |
| A new privacy regulation now covers data you didn't previously have to protect | Sensitive Data Discovery & Classification — scanning production databases for where PII, PHI, or PCI actually lives |
| You bought a governance or catalog tool and never finished configuring it | Sensitive Data Discovery & Classification — classification wired into access policy, not a one-time spreadsheet |
| Access requests get handled ad hoc, with no consistent policy behind them | Access Control Engineering — least-privilege policy enforced at the database, not documented in a wiki |
Decisions We Help You Get Right
Securing production data comes with its own set of tradeoffs. Here's how we think through the ones that come up most.
Database-native controls vs. an enterprise governance platform
Collibra, Immuta, and BigID carry a significant annual license cost, and the most common failure mode is paying for the platform and never configuring the workflows that make it useful. Postgres row-level security, masking views, and Vault-managed credentials solve the same problem for most teams at a fraction of the cost. We size the decision to your actual data footprint, not the vendor's pitch deck.
Which framework to satisfy first, when more than one applies
SOC 2, HIPAA, and PCI-DSS overlap on access control, encryption, and audit logging by a wide margin: the differences are in scope and retention period, not the underlying engineering. We sequence around whichever audit date or regulatory deadline is actually on your calendar, and the overlap means the second framework costs far less than the first.
Encrypt everything vs. targeted field-level encryption
Blanket application-layer encryption on every column sounds safer but adds query complexity, breaks indexing on encrypted fields, and slows down every read. Targeting the specific columns that hold regulated data (SSNs, PHI fields, payment card numbers) gets the same compliance outcome without rewriting your entire data access layer.
We implement the controls vs. your team executes our design
Some clients want the exposure assessment and control design, then implement it with their own engineers. Others want us to build the row-level security policies and encryption directly, especially against an audit deadline. Both are normal outcomes of the same engagement. The design doesn't change based on who writes the migration.
Why Engineer the Control Before You Buy the Platform
Engineering, Not Paperwork
We implement row-level security, column masking, encryption, and audit logging directly in your database and data stack, not a policy binder that sits next to a catalog tool nobody updates.
Built to Survive the Audit You Actually Have
SOC 2, HIPAA, PCI-DSS, or a customer's security questionnaire: we map each requirement to the specific system it governs, so gathering evidence is a query, not a scramble.
Sized to Your Real Exposure
Most companies don't need a costly enterprise governance platform. We'll tell you when a database-native control (Postgres RLS, a masking view, Vault-managed credentials) solves it instead.
Frameworks We Map to Technical Controls
Tell us which framework you're working toward. These are the specific engineering requirements each one actually tests, not the compliance-101 version.
SOC 2 (Type I/II)
Access control evidence tied to specific roles, audit logging retained across the observation window, encryption in transit and at rest, and change-management logs for every schema or permission change: the controls an auditor samples directly.
HIPAA
PHI encryption at rest and in transit, "minimum necessary" access enforced through RBAC and row-level security rather than a policy document, audit controls under §164.312(b), and a 6-year audit log retention requirement.
GDPR / CCPA / CPRA
A right-to-erasure pipeline that actually reaches the primary database, replicas, backups, and caches (not just the row in the main table), plus data minimization at the schema level and consent-linked access controls.
PCI-DSS
Cardholder data environment scoping, PAN tokenization or masking so raw card numbers don't sit in plaintext, encryption key management with rotation, and access logging on every query that touches the CDE.
Four Parts of Every Data Governance & Security Engagement
Sensitive Data Discovery & Classification
Scan production databases and warehouses to find where PII, PHI, or PCI data actually lives, not where you assume it lives, tag it, and wire that classification into access policy, not a one-time spreadsheet.
Access Control Engineering
Row-level security in Postgres or Snowflake row access policies, column-level masking and tokenization, and RBAC/ABAC redesigned around least privilege, enforced at the database, not documented in a wiki.
Encryption & Secrets Overhaul
Field-level encryption for the columns that need it, KMS-backed key management, and dynamic, short-lived database credentials via Vault or your cloud provider's secrets manager instead of static passwords in an env file.
Audit Logging, Retention & Deletion Engineering
Database activity monitoring and audit trails that actually answer who accessed what and when, plus a real retention and right-to-erasure pipeline that reaches primary databases, replicas, backups, and caches.
Specific Situations This Solves
First enterprise deal, first security questionnaire
A Series A/B SaaS company closes its first large customer, and the questionnaire asks for row-level access control and audit logging that don't exist yet.
SOC 2 Type II renewal with drifted controls
Controls passed Type I a year ago; grants have accumulated since, and nobody's re-reviewed who can touch what.
HIPAA gap before a health-data partnership
A platform is adding PHI for the first time and needs encryption, access control, and a 6-year audit log retention path before data starts flowing.
PCI-DSS scoping for a new payments feature
Card data is about to enter the database, and the cardholder data environment needs tokenization and access logging before launch.
A governance platform license sitting unused
Collibra, Immuta, or BigID was purchased for a compliance push, and the workflows were never configured, so the license renews without solving anything.
A deletion request that didn't actually delete anything
A right-to-erasure request cleared the primary table but left the row in a replica, a backup, or a cache, surfaced by an audit or a customer complaint.
What Happens After You Reach Out
Exposure & compliance-gap assessment
An audit of where sensitive data actually lives, who can access it, what's encrypted, what's logged, and which specific control gaps block your target framework.
Control design
We map each compliance requirement to a specific technical control (an RLS policy, a masking view, a KMS key, an audit table), scoped to your actual stack, not a generic framework binder.
Pilot implementation
We build and ship the highest-risk control first, usually access control or encryption, so you have something an auditor or customer security team can verify, not a roadmap.
Evidence & documentation handoff
We package the audit logs, access policies, and encryption configuration as auditor-ready evidence, and train your team to maintain it without us in the room.
Ongoing monitoring & support
On retainer, we run continuous drift detection (a new unencrypted column, a newly over-broad grant) so the control set doesn't quietly rot between audits.
Before → After
The same four areas, measured before and after the engagement.
| Area | Before | After |
|---|---|---|
| Discovery | Sensitive data classified once in a spreadsheet, never re-scanned as schemas change | Classification wired into access policy, re-checked as schemas evolve |
| Access control | Permissions granted ad hoc, rarely revoked | Least privilege enforced as a database grant (RLS, masking), not a policy sentence |
| Encryption & secrets | Static database passwords in an env file | KMS-backed field encryption and short-lived credentials via Vault or a cloud secrets manager |
| Audit & retention | Deletion clears the primary table, not the replica, backup, or cache | Retention and right-to-erasure pipeline reaches every copy of the data |
In one engagement, a healthcare platform closed audit-log gaps and added continuous replication ahead of a HIPAA-covered telehealth launch.
How This Differs From the Alternatives
| Option | Fit | Cost shape |
|---|---|---|
| DharmOps | Engineers the control directly in your stack | Scoped per control area, sized to real exposure |
| Enterprise governance platform (Collibra, Immuta, BigID) | Strong once workflows are configured and maintained | Significant annual license, plus the implementation work most teams underbudget |
| Fractional CISO | Sets the security program and risk posture | Advisory, doesn't write the RLS policy or encryption config itself |
| Full-time database security hire | Good fit once control work is continuous, not project-shaped | Full-time salary and benefits for often project-shaped work |
Data Governance & Security Use Cases by Industry
Each regulation tests a different set of controls. We build the controls the audit checks, mapped to the framework that applies to you.
Data Governance & Security for FinTech
PCI DSS 4.0 expects automated controls that alert on unexpected data flows. We limit cardholder data access to need-to-know and add monitoring for movement outside approved paths.
Data Governance & Security for Banking & Insurance
Examiners ask who accessed what and when. We build access certification, encryption with key management, and retention rules that produce that evidence from logs.
Data Governance & Security for SaaS & Software
SOC 2 reviews turn on tenant isolation and access control. We enforce them in the database layer and generate the access and change evidence the auditor requests.
Data Governance & Security for Retail & eCommerce
GDPR and CCPA deletion requests span the warehouse, backups, and downstream copies. We build the discovery and deletion pipeline so a request is honored everywhere.
Data Governance & Security for Enterprise Businesses
AI and analytics tools now reach data that was never classified. We extend access policies and audit logging to those tools before they connect to sensitive tables.
Data Infrastructure Engineering for 13 Industries
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Often Paired With
Data Engineering
Governance engineering sets the access rules; platform engineering enforces them inside the golden path, so self-service provisioning doesn't mean unrestricted access.
Database Engineering
Governance engineering defines access policy and audit requirements; an ongoing database engineering retainer is where that policy gets maintained and monitored for drift day to day.
Data Modernization
Governance is hardest to retrofit after the fact; modernization projects are the moment to build access control and encryption in from the start instead of layering it on later.
Frequently Asked Questions
Find Out What an Auditor Would Actually Find
Tell us which framework you're working toward (SOC 2, HIPAA, PCI-DSS, GDPR) or what a customer's security questionnaire just asked you, and we'll tell you honestly which controls are missing and which ones you already have covered.
A Checklist Doesn't Build the Encryption
Most teams that come to us already have the compliance framework mapped out. What's missing is the row-level security policy, the encryption, and the deletion pipeline the framework assumes exists. We build those.