A tailored course, built for your situation
Mastering ISO 27018 for Senior Data Engineers in Regulated Industries
Build privacy-embedded data workflows that stand up to scrutiny, without slowing innovation.
$199 one-time
24-hour access provisioning
30-day money-back guarantee
Hand-built implementation playbook
12 modules. 12 chapters per module. 144 chapters total.
12 modules, each with 12 chapters (144 chapters total), text-based, plus downloadable templates and a hand-built implementation playbook delivered alongside course access.
Audit packages requiring last-minute rework due to inconsistent PII handling
The situation this course is for
Senior data engineers in regulated environments routinely face intense pre-audit pressure when privacy controls aren't embedded at the pipeline level. The result: rework, delayed launches, and fragile documentation that doesn't reflect actual data flows.
Who this is for
Senior Data Engineer in a data-intensive, compliance-aware tech environment (e.g., cloud data platform, fintech, healthtech) responsible for designing, documenting, and defending data workflows under privacy and security scrutiny.
Who this is not for
Junior engineers learning SQL, analysts focused on reporting, or compliance staff without data pipeline ownership. This course presumes hands-on dbt and Snowflake experience, but is not about mastering the platform itself.
What you walk away with
- Design data pipelines with ISO 27018 controls natively embedded
- Produce audit-ready documentation that reflects real architecture
- Reduce pre-audit validation cycles by 90% or more
- Respond confidently to regulator follow-ups with traceable flows
- Standardize PII handling across teams without centralizing control
The 12 modules (with all 144 chapters)
Module 1. ISO 27018 Fundamentals for Data Engineers
Understand the core requirements of ISO 27018 and how they map directly to data pipeline design choices, not just documentation.
12 chapters in this module
- What ISO 27018 is and why it matters for cloud data platforms
- Difference between ISO 27001 and ISO 27018 in practice
- Core obligations for personal data in public cloud environments
- Role of the data processor vs. data controller in Snowflake contexts
- How privacy commitments cascade from contract to code
- Common misconceptions about data residency and replication
- Mapping clauses to data handling patterns
- Why traditional logging breaks privacy expectations
- Audit scope for cloud data warehouses: what’s in, what’s out
- How regulators assess compliance in distributed systems
- Key differences from GDPR in enforcement context
- Preparing for cross-border data flow challenges
Module 2. Privacy by Design in Data Modeling
Embed privacy into table structures, naming conventions, and transformation logic from day one.
12 chapters in this module
- Schema design patterns that signal PII status clearly
- Column-level tagging strategies in dbt and Snowflake
- Naming conventions that enforce privacy discipline
- Role-based access patterns at the model layer
- Documenting data lineage with privacy in mind
- Automating PII detection in new models
- Designing views to mask sensitive data by role
- Handling derived PII in aggregates and metrics
- When to split tables for privacy vs. performance
- Partitioning strategies for data residency compliance
- Versioning sensitive models without exposing history
- Validating privacy design in pull requests
Module 3. Data Pipeline Controls for ISO 27018
Implement technical controls at each stage of the pipeline to meet processor obligations.
12 chapters in this module
- Ingestion: validating source data against privacy notices
- Metadata extraction with privacy context retained
- Transformation: avoiding accidental PII creation
- Temporary tables and scratch space handling
- Error logging without exposing personal data
- Pipeline monitoring that respects data minimization
- Handling failed records without creating backdoors
- Automated redaction during stage processing
- Secure data sharing patterns between environments
- Retention policies in staging and transient layers
- Cross-account pipeline security settings
- Audit logging for pipeline changes
Module 4. Access Governance in Practice
Design role-based access that satisfies auditors while supporting agile development.
12 chapters in this module
- Role hierarchy design for data teams and consumers
- Dynamic masking policies in Snowflake
- Row-level security for multi-tenant data sets
- Time-bound access for incident investigations
- Least privilege principles in dbt models
- Managing access for vendor partners securely
- Automated deprovisioning workflows
- Audit trail generation for access changes
- Secrets management in CI/CD pipelines
- Credential rotation without breaking pipelines
- Detecting privilege creep in data roles
- Standardizing access requests across teams
Module 5. Audit-Ready Documentation Patterns
Generate living documentation that reflects actual data flows and satisfies external reviewers.
12 chapters in this module
- Automating data inventory from dbt manifests
- Linking models to privacy notices and contracts
- Versioned data flow diagrams that stay updated
- Documenting data lineage with ownership tags
- Generating compliance evidence from code
- Maintaining data dictionaries with PII flags
- Self-updating control matrices from pipeline metadata
- Integrating documentation into CI/CD gates
- Standardizing review cycles for compliance
- Preparing for regulator walkthroughs
- Building trust with internal audit teams
- Closing the loop between findings and fixes
Module 6. Cross-Team Privacy Alignment
Align data engineering, legal, and security teams around shared privacy goals.
12 chapters in this module
- Translating legal requirements into technical specs
- Creating shared definitions of personal data
- Onboarding legal reviewers to data workflows
- Building feedback loops with DPOs
- Managing conflicts between utility and privacy
- Handling exceptions without creating precedent
- Standardizing cross-functional review templates
- Running privacy triage for new projects
- Escalation paths for ambiguous cases
- Documenting decisions for future reference
- Training non-engineers on pipeline basics
- Measuring team alignment on privacy goals
Module 7. PII Detection and Classification
Implement accurate, maintainable systems to identify personal data across large datasets.
12 chapters in this module
- Defining personal data in your domain context
- Pattern matching for common PII types
- Statistical methods to detect unknown PII
- Integrating classification into ingestion pipelines
- Handling false positives gracefully
- Versioning PII detection rules
- Auditing classification accuracy over time
- Combining rule-based and ML approaches
- Managing edge cases like nicknames and codes
- Documenting uncertainty in classification
- Sharing detection logic across teams
- Updating rules in response to findings
Module 8. Data Retention and Deletion Workflows
Design automated systems to meet deletion obligations without breaking referential integrity.
12 chapters in this module
- Mapping retention policies to business needs
- Anchoring retention on primary entities
- Cascading deletion across related models
- Handling soft deletes in analytics models
- Archiving vs. deletion decision trees
- Automated data purging in Snowflake
- Validating deletion completeness
- Managing audit exceptions for deletion
- Retention tagging in dbt models
- Cross-system coordination for deletion
- Testing deletion workflows safely
- Documenting data lifecycle decisions
Module 9. Incident Response for Data Teams
Prepare to respond quickly and correctly when privacy incidents occur.
12 chapters in this module
- Defining incident types relevant to data engineers
- Initial triage steps for data exposure
- Containment strategies for live pipelines
- Preserving evidence without disrupting service
- Coordinating with security and legal teams
- Generating incident timelines from logs
- Assessing scope of data exposure
- Identifying affected individuals accurately
- Communicating technical details clearly
- Post-mortem documentation standards
- Updating controls to prevent recurrence
- Stress-testing response plans
Module 10. Privacy Testing and Validation
Build automated checks that catch privacy issues before deployment.
12 chapters in this module
- Unit testing for PII handling logic
- Integrating privacy checks into dbt tests
- Automated scans for hardcoded credentials
- Validating access policies in staging
- Penetration testing for data pipelines
- Fuzz testing input validation layers
- Performance testing under privacy constraints
- Auditing pipeline changes for PII impact
- Red team exercises for data exposure
- Measuring test coverage for privacy controls
- Benchmarking against peer organizations
- Reporting test results to leadership
Module 11. Vendor and Partner Data Flows
Secure data sharing with third parties while maintaining compliance.
12 chapters in this module
- Assessing vendor privacy posture objectively
- Data processing agreements checklist
- Secure sharing patterns in Snowflake
- Managing access for external partners
- Auditing vendor data usage
- Handling data return and deletion
- Monitoring for unauthorized redistribution
- Incident response with third parties
- Onboarding new vendors securely
- Standardizing data sharing requests
- Documenting data flows to partners
- Evaluating sub-processor risks
Module 12. Scaling Privacy Across the Organization
Extend privacy practices to all data teams without bottlenecks.
12 chapters in this module
- Creating reusable privacy components
- Template-based model generation
- Internal developer education programs
- Privacy linting tools for CI/CD
- Centralized policy with decentralized enforcement
- Measuring adoption across teams
- Sharing best practices without mandates
- Building internal communities of practice
- Reducing friction for compliant development
- Tracking maturity over time
- Integrating with enterprise architecture
- Planning for future regulations
How this maps to your situation
- Pre-audit preparation
- Regulator follow-up response
- Cross-team workflow alignment
- Incident readiness
Before vs. after
Before
Spending weeks reconciling documentation with actual data flows before audits, reacting to findings, and explaining gaps to legal teams.
After
Producing clean, defensible outputs the first time, validating compliance in hours, not days, with confidence in every pipeline.
What's included with your purchase
- 12 modules with 12 chapters each (144 chapters)
- Downloadable templates and worked examples for every module
- Hand-built implementation playbook delivered alongside course access
- 30-day money-back guarantee
Delivery and format
- Course and learning environment access provisioned within 24 hours of purchase
- Hand-built implementation playbook delivered alongside course access
Format: Text-based modules and chapters in the Art of Service learning environment, plus downloadable templates and worked examples for every chapter, plus the hand-built implementation playbook delivered alongside course access.
Time investment: 90 minutes per week over 4 weeks, with flexible access for review and implementation.
If nothing changes
Continuing to rely on manual documentation and reactive fixes risks repeated audit findings, delayed product launches, and erosion of trust with legal and security partners.
How this compares to the alternatives
Unlike generic compliance courses, this is tailored to the daily work of senior data engineers, focusing on code, pipelines, and documentation patterns that stand up to real audits.
Frequently asked
Is this course about Snowflake?
No. It's about building privacy-compliant data pipelines in cloud environments, using patterns applicable to any platform. Examples are drawn from Snowflake contexts but are not about the tool itself.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Will this help me pass an ISO 27018 audit?
Yes. The course teaches how to build systems and documentation that meet ISO 27018 requirements, with auditable evidence built into your workflows.
$199 one-time. 90 minutes per week over 4 weeks, with flexible access for review and implementation..
Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.
30-day money-back guarantee·
144 chapters·
Hand-built playbook included·
Account access within 24 hours