Smart Scaling: How a Healthcare Provider Governed 100K+ Columns of Sensitive Data in Two Weeks — at 10x Less Than SaaS
Automated HIPAA/HITECH compliance without the headcount
Tony Zeljkovic
2025-03-10
- Industry: Healthcare
- Duration: ~1 quarter (2-week initial deployment, full rollout by end of quarter)
- Team: 1–2 Narona Data consultants
- Stack: Snowflake, dbt, custom IaC, VS Code devcontainers, CI/CD
- Key Results: 100K+ columns masked | 10K+ tables governed | 2-week deployment | ~10x cheaper than SaaS alternatives
Executive Summary
A mid-size U.S. healthcare provider needed to open data access across the organization — but HIPAA/HITECH compliance made every new connection a governance problem. Off-the-shelf SaaS solutions quoted multiple six figures annually. Narona Data delivered an automated, tag-based data masking system in Snowflake that governed 100K+ columns across 10K+ tables, deployed in two weeks and fully rolled out within a quarter — for a fraction of the SaaS price.
Situation
A growing U.S. healthcare company operated a central data platform on Snowflake and dbt, maintained by a lean data platform team. The infrastructure was solid, and the team was technically capable.
But data access was tightly controlled. Only a small set of data-adjacent roles could use the platform directly. Engineering teams, analysts, and business units wanted more access — and the company had untapped potential in self-service analytics and new data-driven platforms.
Complication
Two pressures made the status quo untenable:
Growth was blocked. The data team couldn't scale access without solving governance first. Every new user or application that touched PII/PHI required manual access provisioning — a process that didn't scale and created compliance risk with every shortcut.
Audit exposure. HIPAA/HITECH compliance required demonstrable, continuous governance over sensitive data. The existing table-level access controls couldn't restrict at the column level without creating an unmanageable number of roles. One audit gap could mean regulatory fines.
Off-the-shelf SaaS governance solutions could address the problem, but quoted at multiple six figures annually — and still required engineering overhead to integrate. The team was budget-constrained and needed a solution that would cost an order of magnitude less while requiring minimal ongoing engineering hours.
Resolution
Narona Data delivered three interventions over a single quarter with a two-person team.
1. Tag-Based Dynamic Data Masking in Snowflake
The core challenge was column-level access control across a massive warehouse — 10K+ tables, 100K+ columns — without creating a role explosion.
Narona Data built a tag-based dynamic data masking system using custom infrastructure-as-code and dbt macros. Tags in dbt YAML files controlled masking at the database, schema, table, and column level. The CI/CD pipeline applied masking automatically on every deployment.
Within two weeks, the system was masking terabytes of data across the full warehouse. No manual role management. No per-table access grants.
Why tag-based: Traditional role-based access at the column level would have required thousands of roles — impossible to maintain. Tag-based masking let the team define policies declaratively in YAML and enforce them automatically through the existing dbt workflow.
2. Developer Experience for Analytics Engineers
Governance systems fail when they're too painful to use. Narona Data built two enablement layers to keep the data team productive:
VS Code devcontainer — A custom development environment with pre-commit hooks that flagged incorrectly defined masking policies before code was committed. Analytics engineers got immediate feedback on compliance errors.
CI/CD enforcement — A custom dbt application that automatically enforced default masking policies, corrected misconfigurations, and tracked any assets not yet covered by the governance system. This meant compliance improved automatically with every deployment, not just when someone remembered to check.
Within four weeks, all tools were deployed and the data team was trained.
3. Phased Rollout Across Applications
Rolling out dynamic data masking across a live warehouse with dependent applications required care. Breaking an application because of an incorrectly applied mask would destroy trust in the new system.
Narona Data configured the system for controlled, phased enrollment. The team mapped every application interacting with the warehouse, then enrolled them incrementally with testing at each iteration.
By end of quarter, all systems were fully migrated and the client was operating independently.
Results
| Metric | Before | After | Business Impact |
|---|---|---|---|
| Data masking coverage | Manual, table-level only | 100K+ columns, 10K+ tables | Column-level compliance across the full warehouse |
| Compliance posture | Manual checks, audit risk | 24/7/365 automated | Continuous HIPAA/HITECH compliance with minimal engineering hours |
| Time to initial deployment | — | 2 weeks | Governance live before the next audit cycle |
| Cost vs. SaaS | Multiple six figures/year quoted | ~10x less | Budget freed for data team growth and new platforms |
| Ongoing maintenance | Would require dedicated headcount | Automated via CI/CD | No new hires needed to maintain governance at scale |
Cost comparison is directional based on vendor quotes vs. engagement cost. Masking coverage is a measured outcome.
Ready to Talk?
Facing compliance challenges that are blocking your data team from scaling? Narona Data offers a free consultation to help you find the right governance approach for your stack.