15 Topics
10 Days
75 Sessions
Programme Overview
Training Description
Who Should Attend
- Data Platform Engineers
- Analytics Engineers
- DevOps Engineers
- MLOps Engineers
- Data Scientists
- Machine Learning Engineers
- Data Governance Professionals
- Data Privacy Professionals
- Information Security Professionals
- IT Managers and Technical Leads
- System and Solutions Architects
- Professionals responsible for building or managing data-intensive systems
Session Objectives
- Understand the legal principles behind GDPR, HIPAA, and related frameworks
- Translate regulatory obligations into engineering requirements
- Design and implement privacy-enhancing technologies in pipelines
- Apply data minimization, pseudonymization, and anonymization techniques
- Build secure data infrastructure aligned with compliance mandates
- Ensure proper consent management and auditing mechanisms
- Implement logging, monitoring, and breach response controls
- Evaluate and document data flows and processing activities
- Use automation tools to enforce privacy compliance
- Design systems with privacy by design and by default
- Collaborate with legal and compliance teams effectively
About the Course
This specialized training course equips engineers and technical professionals with the knowledge and practical skills required to embed data privacy, governance, security, and responsible data management into modern data and software systems. It focuses on translating privacy and governance requirements into practical engineering controls throughout the data lifecycle.Participants will explore data classification, data ownership, privacy-by-design, access control, encryption, data retention, consent management, data minimization, metadata, lineage, data quality, auditability, and regulatory compliance. The course emphasizes how engineers can incorporate governance requirements into data pipelines, databases, APIs, cloud platforms, data lakes, warehouses, lakehouses, analytics systems, and AI/ML environments.
Through practical exercises and real-world scenarios, participants will learn how to identify sensitive data, assess privacy risks, implement appropriate technical controls, manage data access, protect data throughout its lifecycle, and build systems that are secure, auditable, compliant, and trustworthy.
Curriculum & Topics
15 Topics | 75 Sessions
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Workshop 1.1:
Overview of global privacy frameworks (GDPR, HIPAA, CCPA)
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Workshop 1.2:
Key definitions and roles: controller, processor, DPO
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Workshop 1.3:
Legal basis for data processing
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Workshop 1.4:
Enforcement bodies and penalties
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Workshop 1.5:
Privacy principles that affect data engineering
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Workshop 2.1:
Article-by-article engineering implications
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Workshop 2.2:
Data subject rights: access, erasure, portability
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Workshop 2.3:
DPIA (Data Protection Impact Assessment) process
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Workshop 2.4:
Lawful basis for data processing
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Workshop 2.5:
Records of processing activities (RoPA)
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Workshop 3.1:
HIPAA structure: Privacy Rule, Security Rule, Breach Notification Rule
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Workshop 3.2:
Protected Health Information (PHI) handling requirements
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Workshop 3.3:
Minimum necessary principle
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Workshop 3.4:
Business associate agreements (BAAs)
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Workshop 3.5:
Security safeguards: administrative, technical, physical
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Workshop 4.1:
Mapping data sources, processing, and storage
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Workshop 4.2:
Identifying sensitive and regulated data
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Workshop 4.3:
Documenting data lineage and access points
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Workshop 4.4:
Tools for automated data discovery and classification
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Workshop 4.5:
Building visual data flow diagrams
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Workshop 5.1:
Embedding privacy into system architecture
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Workshop 5.2:
Minimization, separation, and abstraction
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Workshop 5.3:
Designing for least privilege and zero trust
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Workshop 5.4:
Secure defaults and opt-in mechanisms
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Workshop 5.5:
Integrating privacy principles into DevOps
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Workshop 6.1:
Strategies for reducing collected and stored data
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Workshop 6.2:
Aggregation and sampling methods
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Workshop 6.3:
Truncation, tokenization, and retention policies
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Workshop 6.4:
Decoupling identifiers from data
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Workshop 6.5:
Impact on analytics and model performance
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Workshop 7.1:
Legal distinctions and practical use cases
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Workshop 7.2:
Techniques for pseudonymizing identifiers
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Workshop 7.3:
k-anonymity, l-diversity, and differential privacy
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Workshop 7.4:
Risks of re-identification
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Workshop 7.5:
Tools and libraries for implementation
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Workshop 8.1:
Encryption at rest and in transit
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Workshop 8.2:
Fine-grained access control (RBAC/ABAC)
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Workshop 8.3:
Key management practices
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Workshop 8.4:
Protecting metadata and logs
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Workshop 8.5:
Hardening data warehouses and lakes
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Workshop 9.1:
Engineering consent capture and withdrawal
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Workshop 9.2:
Storing consent as metadata
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Workshop 9.3:
Consent-aware processing and querying
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Workshop 9.4:
Integration with marketing and CRM systems
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Workshop 9.5:
User interfaces for privacy preferences
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Workshop 10.1:
Designing ETL/ELT for compliance
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Workshop 10.2:
Redacting, masking, and filtering sensitive fields
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Workshop 10.3:
Managing transient vs. persistent data
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Workshop 10.4:
Metadata tagging for compliance tracking
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Workshop 10.5:
Audit logging and lineage in pipelines
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Workshop 11.1:
Real-time monitoring and alerting frameworks
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Workshop 11.2:
Retention and analysis of access logs
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Workshop 11.3:
Data breach response workflows
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Workshop 11.4:
Regulatory notification timelines
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Workshop 11.5:
Post-breach audit and reporting
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Workshop 12.1:
Managing processors and service providers
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Workshop 12.2:
Security questionnaires and risk assessments
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Workshop 12.3:
Data sharing agreements and SLAs
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Workshop 12.4:
Evaluating vendor compliance certifications
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Workshop 12.5:
Privacy risks in SaaS, IaaS, and APIs
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Workshop 13.1:
Using policy-as-code for privacy rules
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Workshop 13.2:
Integrating with CI/CD pipelines
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Workshop 13.3:
Privacy testing in staging environments
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Workshop 13.4:
Self-healing data workflows
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Workshop 13.5:
Building alerts for non-compliance
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Workshop 14.1:
Automating DSAR responses (SAR, deletion, rectification)
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Workshop 14.2:
Connecting data sources for holistic views
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Workshop 14.3:
Authentication and verification workflows
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Workshop 14.4:
Data export formats and channels
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Workshop 14.5:
Tracking and logging fulfillment timelines
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Workshop 15.1:
Legal mechanisms for international data transfers
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Workshop 15.2:
Standard contractual clauses (SCCs) and adequacy decisions
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Workshop 15.3:
Geolocation and residency controls
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Workshop 15.4:
Multi-region architecture considerations
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Workshop 15.5:
Building a privacy compliance roadmap
