Data Engineering – Persona: Navigating regional compliance & identity laws
This is a guest post for the Computer Weekly Developer Network written by Persona CTO, Charles Yeh.
Persona is known for its platform technology designed to provide identity verification, allowing businesses to collect, verify and manage user identities by checking if individuals are who they claim to be… it is often used to combat fraud and ensure compliance with regulations.
Yeh writes in full as follows…
Data compliance has never been more critical – or more complex.
Regional (and international) regulations around data privacy, protection and identity management are constantly evolving, presenting significant challenges for organisations operating in multiple jurisdictions. From GDPR in Europe to CCPA in California and emerging frameworks like India’s DPDP Act, companies must navigate a labyrinth of legal requirements to avoid fines and maintain customer trust.
To ensure compliance with evolving regulation requires significant work at data level.
Building robust, scalable systems to collect, process and manage data, organisations ensure that businesses meet legal obligations while enabling efficient operations. This serves as the foundation for regional and international compliance efforts, balancing the need for transparency and control with the operational realities of global businesses.
Without data engineering, compliance fails
There are three pillars to a strong data foundation: accuracy, accessibility and accountability. Without these, meeting compliance standards becomes a logistical nightmare – so data engineering can help organisations address:
- Data Localisation Differences: While not all regions require data to be stored within their borders, many impose strict requirements on how data from their residents is handled. Data engineers design pipelines and storage systems that ensure data is managed according to specific geographic regulations, enabling companies to adhere to laws like the California Consumer Privacy Act (CCPA) or the Iowa Consumer Data Protection Act (ICDPA). For instance, the CCPA grants California residents extensive rights over their data, requiring systems that can quickly identify and manage a resident’s information, while the ICDPA mandates specific security measures for Iowa residents’ data, effectively creating a form of functional data localisation.
- Identity-Centric Design: Regulations like GDPR and the ePrivacy Directive emphasise protecting personal data and identities. Data engineers build systems that separate personally identifiable information (PII) from other datasets, reducing exposure and simplifying compliance audits.
- Consent Management: Modern data laws place heavy emphasis on consent. Data engineers create systems that track user preferences in real-time, ensuring that businesses respect opt-ins and opt-outs at every touchpoint. These systems also log consent histories, creating an audit trail for regulators.
- Data Minimisation and Retention Policies: Many compliance frameworks mandate that businesses collect only what they need and delete data once it’s no longer required. Automated workflows built by data engineers ensure unnecessary data beyond its useful lifespan is redacted.
The backbone of compliance
Data engineering enables organisations to meet the growing complexities of compliance and identity management in a number of ways:
- Data Localisation & Residency: Laws like Russia’s data localisation requirements and Brazil’s LGPD mandate that certain types of data remain within national borders. Data engineers design pipelines to store and process data in region-specific clouds or on-premises infrastructure, ensuring adherence to local laws without disrupting operations.
- Identity Protection Through Encryption and Masking: Identity-centric regulations emphasise protecting personally identifiable information (PII). Data engineers implement encryption and tokenization to safeguard PII both in transit and at rest. Masking sensitive data during analysis ensures privacy while still allowing valuable insights to be drawn.
- Consent and Preference Management: Laws like GDPR require explicit consent for collecting and processing personal data. Data engineers build systems to log consent in real-time and automate preference changes, creating an auditable trail for regulators. This ensures organisations stay compliant while respecting user rights.
- Data Minimisation and Retention Policies: Compliance frameworks often mandate collecting only what’s necessary and deleting data once it’s no longer needed. Data engineers automate retention policies, ensuring expired data is deleted or archived in compliance with regional rules while maintaining operational efficiency.
- Real-Time Monitoring & Incident Reporting: Regulations frequently require organisations to report data breaches within specific time frames (e.g., 72 hours under GDPR). Data engineers enable real-time monitoring systems to detect anomalies, trigger alerts and compile detailed reports, ensuring timely responses to security incidents.
From compliance to operational excellence
Embedding strong data engineering practices into processes, organisations can streamline workflows, minimise redundancies and build greater trust with their customers.
Automated audit trails are a prime example. These systems generate detailed logs of every data interaction, making audits straightforward and reducing the burden on compliance teams. Instead of scrambling to piece together information during a review, organisations have a clear, ready-made record of their practices.
Scalable frameworks can also enable businesses to adapt to new regulations without the need for major overhauls. Flexible data pipelines allow teams to integrate new requirements seamlessly, ensuring compliance remains manageable even in a shifting regulatory landscape.
All of this boosts transparency. With systems that provide clear, accessible records of data usage, organisations can demonstrate to users that their information is handled responsibly.