LGPD for Developers: What Brazil's Data Protection Law Actually Means for Your Code

If you're building software that touches Brazilian users' data, you need to understand LGPD. Not as a legal checkbox — as an architectural constraint that shapes how you write code.

Brazil's Lei Geral de Proteção de Dados (LGPD), enacted in 2020, is often compared to GDPR. That comparison is accurate but incomplete. LGPD has its own nuances, its own enforcement patterns, and its own practical implications for developers working in the Brazilian market.

At Mind Group Technologies, we've been building LGPD-compliant systems since the law was enacted. We work across healthcare, fintech, and SaaS — three verticals where data protection isn't optional; it's existential. Here's what we've learned about translating legal requirements into actual code.

The Core Principles (In Developer Terms)

LGPD has 10 legal bases for processing personal data. But in practice, most developers need to think about three things:

1. Purpose Limitation
You can only collect data for a specific, declared purpose. In code terms: if your user signs up to receive a newsletter, you can't use their email for marketing campaigns without separate consent.

// BAD: Collecting data without clear purpose
const userData = {
  name: req.body.name,
  email: req.body.email,
  cpf: req.body.cpf,        // Why do you need CPF for a newsletter?
  phone: req.body.phone,    // Why do you need phone for a newsletter?
  address: req.body.address  // Definitely don't need this
};

// GOOD: Data minimization
const userData = {
  email: req.body.email,
  consent_newsletter: true,
  consent_timestamp: new Date().toISOString(),
  consent_version: 'v2.1'
};

2. Data Minimization
Collect only what you need. This sounds obvious but watch how many registration forms ask for CPF, full address, and phone number when all they need is an email.

3. Right to Deletion
Users can request that you delete their data. This means your database schema needs to support actual deletion — not just soft deletes that leave data in your tables forever.

Consent Management: The Technical Implementation

LGPD requires explicit, granular consent. Here's what that looks like in practice:

// Consent record structure
const consentRecord = {
  user_id: 'uuid',
  consents: [
    {
      purpose: 'email_marketing',
      granted: true,
      timestamp: '2026-02-13T10:30:00Z',
      version: 'privacy_policy_v3.2',
      method: 'checkbox_signup_form',
      ip_address: '189.x.x.x'
    },
    {
      purpose: 'analytics_tracking',
      granted: false,
      timestamp: '2026-02-13T10:30:00Z',
      version: 'privacy_policy_v3.2',
      method: 'cookie_banner',
      ip_address: '189.x.x.x'
    }
  ]
};

Key implementation details:

• Versioned consent: When your privacy policy changes, previous consents need to be re-obtained. Track which version each consent was given under.
• Granular opt-in: Don't use a single "I agree to everything" checkbox. Each purpose needs its own consent toggle.
• Audit trail: Every consent grant and revocation must be logged with timestamp, method, and context.

The Deletion Problem: Harder Than You Think

When a user requests data deletion, you need to delete their data from:

• Your primary database
• All replicas and read replicas
• Backup systems (within reasonable timeframe)
• Log files (PII should never be in logs)
• Third-party services you've shared data with
• Cache layers (Redis, CDN)
• Search indexes (Elasticsearch, Algolia)
• Analytics systems
• Email marketing platforms

At Mind Group Technologies, we built a deletion pipeline that handles this systematically:

User Request → Validation → Primary DB Delete → 
Queue Async Jobs → [Cache Purge, Search Index Update, 
Third-Party API Calls, Log Scrubbing] → 
Confirmation Email → Audit Log Entry

The async jobs are critical. You can't wait for Elasticsearch to re-index and your email provider to process the deletion before responding to the user. Queue these as background jobs with retry logic and dead-letter queues for failures.

Encryption: At Rest and In Transit

LGPD doesn't specify encryption algorithms, but the ANPD (Brazil's data protection authority) has made it clear that encryption is expected for sensitive data.

At rest: AES-256 for database fields containing PII. Don't encrypt everything — that kills query performance. Encrypt sensitive fields: CPF, health records, financial data, biometric data.

In transit: TLS 1.2+ for all API communications. This should be table stakes in 2026, but you'd be surprised how many internal services still communicate over plain HTTP.

Key management: Don't store encryption keys in the same database as the encrypted data. Use AWS KMS, HashiCorp Vault, or similar. Rotate keys periodically.

Healthcare and Fintech: Extra Requirements

If you're building in healthcare or fintech, LGPD's "sensitive data" provisions add additional layers:

Healthcare: Patient data (health records, diagnoses, prescriptions) is classified as sensitive personal data. Processing requires explicit consent AND a legitimate purpose. At Mind Group, our healthcare systems implement:

• Field-level encryption for diagnoses and prescriptions
• Role-based access (doctors see clinical data; billing sees only billing data)
• Automatic data retention policies (some records must be kept for 20 years; others should be purged after treatment)

Fintech: Financial transaction data requires:

• Immutable audit logs (append-only tables)
• Transaction-level access controls
• PCI-DSS compliance layered on top of LGPD

Common Mistakes We See

After eight years building compliant systems at Mind Group Technologies, here are the most common LGPD mistakes:

1. Logging PII: Your application logs should NEVER contain CPF, email addresses, or any PII. Use UUIDs for log correlation. Scrub PII from error messages before they reach your logging system.

2. Storing consent in cookies: Cookies are not a valid consent record. Cookies expire, get cleared, and can't be audited. Store consent in your database.

3. Ignoring third-party data flows: When you send user data to an analytics platform, an email provider, or a payment processor, YOU are still responsible for that data under LGPD. Map all your data flows.

4. "Soft delete" instead of actual deletion: When a user requests deletion, a deleted_at timestamp is not enough. The data needs to be actually removed or anonymized beyond recovery.

5. No data processing inventory: LGPD requires you to know WHAT data you collect, WHERE it's stored, WHO has access, and WHY. Build a data map before you need one.

Practical Checklist for Developers

If you're building a new application for the Brazilian market:

• [ ] Implement granular consent management with versioning
• [ ] Add field-level encryption for sensitive PII
• [ ] Build a data deletion pipeline (primary DB + all downstream systems)
• [ ] Remove PII from all log outputs
• [ ] Map all third-party data flows
• [ ] Implement role-based access controls
• [ ] Set up data retention policies with automated enforcement
• [ ] Create a data processing inventory document
• [ ] Add cookie consent banner with reject option
• [ ] Implement right to data portability (export user data as JSON/CSV)

The Business Case for Compliance

LGPD fines can reach 2% of revenue (up to R$50 million per violation). But the real cost of non-compliance is losing enterprise clients who require LGPD compliance from their vendors.

At Mind Group Technologies, our LGPD compliance has become a competitive advantage. When we pitch to healthcare companies, hospitals, and fintech firms, being able to demonstrate compliant architecture from day one closes deals faster than any feature demo.

If you're building for the Brazilian market, treat LGPD as a feature, not a burden. Your future enterprise customers will thank you.

José Gonçalves is the Founder of Mind Group Technologies, a software company based in Sorocaba, São Paulo, Brazil. Mind Group builds LGPD-compliant systems across healthcare, fintech, and SaaS verticals.