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SEC0916 Mastering ISO 27001 for Data Engineers in AWS Environments

$199.00
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A tailored course, built for your situation

Mastering ISO 27001 for Data Engineers in AWS Environments

Build unshakable data integrity with a command of the framework that audit panels trust

$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.

Who this is for

Mid-senior Data Engineer in a global systems integrator, working with AWS-hosted data pipelines under compliance mandates

Who this is not for

Entry-level data analysts, DevOps-only engineers without data pipeline ownership, or practitioners outside cloud-hosted compliance environments

What you walk away with

  • Map ISO 27001 controls directly to AWS services and IAM configurations
  • Produce evidence artifacts proactively, no last-minute scrambles
  • Anticipate auditor questions on data classification and encryption boundaries
  • Design pipelines with compliance baked into schema and logging layers
  • Own the narrative when control gaps are flagged, backed by documented design logic

The 12 modules (with all 144 chapters)

Module 1. Foundations of ISO 27001 in Data-Centric Organizations
Understand how information security governance applies specifically to data engineering teams managing distributed systems. This module breaks down the core tenets of ISO 27001 with a focus on data lifecycle ownership, regulatory context for service providers, and the role of engineers in evidence generation. You’ll learn to distinguish operational ownership from control ownership and identify where your influence begins.
12 chapters in this module
  1. Defining information security in data pipeline contexts
  2. How service providers like CGI are redefining control ownership
  3. The difference between security posture and evidence readiness
  4. Mapping data roles to ISO 27001 responsibility clauses
  5. Understanding auditor mindset and expectations
  6. The growing weight of evidence integrity in review cycles
  7. Why engineers now lead compliance architecture discussions
  8. How AWS complexity amplifies documentation demands
  9. From checklist follower to control designer
  10. Case example: Data classification misalignment in a cloud migration
  11. The role of IAM policies in access control assertions
  12. Building audit readiness into daily pipeline design
Module 2. AWS Architecture and ISO 27001 Control Boundaries
Learn how to align AWS infrastructure design with ISO 27001’s control domains, especially A.8, A.9, A.12, and A.13. This module maps specific AWS services (S3, KMS, CloudTrail, IAM, VPC) to control clauses, showing how configuration decisions directly satisfy or undermine compliance. You’ll practice identifying evidence-rich artifacts and structuring them for audit panels.
12 chapters in this module
  1. Matching AWS services to ISO 27001 control domains
  2. S3 bucket policies as evidence of access control
  3. KMS key rotation and encryption logging requirements
  4. Using CloudTrail for operational audit trails
  5. IAM roles and privilege separation in data pipelines
  6. VPC design and network segmentation for compliance
  7. Tagging strategies that support asset inventories
  8. Detecting configuration drift with automated checks
  9. Mapping multi-account setups to control ownership
  10. Documenting evidence flow from AWS to auditor
  11. Avoiding common gaps in cloud-native compliance
  12. Designing for portability across review cycles
Module 3. Data Classification and Handling Under ISO 27001
Explore how data engineers define, track, and protect classified data across pipeline stages. This module provides a practical framework for applying data handling rules under A.8.2 and A.10, showing how schema design, logging, and transformation logic can enforce classification boundaries. You’ll build a data tagging model that satisfies both engineering and auditor needs.
12 chapters in this module
  1. Defining data classification in pipeline contexts
  2. Mapping classification levels to handling requirements
  3. Schema design choices that reinforce classification
  4. Logging only what’s needed for compliance and traceability
  5. Encryption strategies by data classification tier
  6. Handling PII in staging and transformation layers
  7. Metadata tagging for compliance tracking
  8. Auditor expectations for data flow documentation
  9. Using AWS resource tags to mirror classification
  10. Automating classification validation in workflows
  11. Cross-border data movement implications
  12. Designing playbooks for classification exceptions
Module 4. Access Control Design for Data Pipelines
Dive into A.9 controls with a focus on role-based access, least privilege, and session management in AWS-hosted data environments. This module teaches how to structure IAM roles, service accounts, and temporary credentials so they map cleanly to auditor requirements. You’ll design a mock pipeline access model that passes control review.
12 chapters in this module
  1. Translating A.9.1 into AWS IAM role structures
  2. Designing least privilege for ETL service accounts
  3. Session expiration and reauthentication in pipelines
  4. Multi-factor authentication for administrative access
  5. Segregation of duties in development and production
  6. Access logging and review frequency requirements
  7. Role chaining risks and mitigation strategies
  8. Temporary credentials and just-in-time access
  9. Service-linked roles and their compliance footprint
  10. Documenting access control decisions for auditors
  11. Common misconfigurations that fail control reviews
  12. Building automated access certification workflows
Module 5. Cryptographic Controls in Data Movement
Cover A.10 requirements as they apply to data engineers managing transit and rest states in AWS. This module details encryption standards, key lifecycle management, and how to prove compliance without compromising pipeline performance. You’ll implement a logging strategy that captures cryptographic integrity.
12 chapters in this module
  1. A.10.1 and its application to data pipelines
  2. Choosing encryption standards for data at rest
  3. S3 server-side encryption and customer-managed keys
  4. KMS key policies and auditing key usage
  5. Key rotation schedules and documentation
  6. Encrypting data in transit within AWS networks
  7. TLS configuration across microservices
  8. Logging encryption configuration changes
  9. Proving cryptographic integrity to auditors
  10. Balancing performance and security in ETL
  11. Handling legacy systems with weak crypto
  12. Mapping cryptographic decisions to control evidence
Module 6. Audit Evidence Design and Automation
Learn how to design data pipelines that generate audit-ready outputs by default. This module focuses on structuring logs, configuration snapshots, and access reports so they satisfy ISO 27001 evidence requirements. You’ll build a checklist for self-validating evidence completeness.
12 chapters in this module
  1. Defining evidence completeness for A.12 controls
  2. Automated configuration snapshots using AWS Config
  3. CloudTrail logging for pipeline operation
  4. IAM policy versioning and change tracking
  5. Storing evidence in immutable S3 buckets
  6. Using Lambda to generate compliance reports
  7. Alerting on evidence gaps before audit cycles
  8. Versioning control documentation
  9. Designing for evidence portability
  10. Integrating evidence checks into CI/CD pipelines
  11. Validating evidence against auditor checklists
  12. Creating a runbook for evidence collection
Module 7. Change Management and Control Integrity
Address A.12.1 and A.12.5 by aligning data pipeline change workflows with auditor expectations. This module teaches how to document changes, approvals, and testing in ways that preserve control integrity. You’ll design a change log structure that survives technical and team turnover.
12 chapters in this module
  1. Aligning change management with A.12.1
  2. Documenting pipeline changes for auditors
  3. Approval workflows that meet control standards
  4. Testing requirements for data transformation updates
  5. Version control and branching strategies
  6. Rollback plans as part of change approval
  7. Change logging in automated deployment pipelines
  8. Proving change control in cloud-native systems
  9. Handling emergency fixes without breaking compliance
  10. Using code reviews to satisfy audit checks
  11. Integrating Jira tickets with change records
  12. Building audit trails for configuration drift
Module 8. Incident Response and Data Pipeline Resilience
Cover A.16 controls as they apply to data disruptions, especially how logs, alerts, and response playbooks satisfy auditor expectations. This module teaches how to structure incident documentation so it supports both recovery and compliance.
12 chapters in this module
  1. Defining incidents in data pipeline operations
  2. A.16.1 and response planning for data failures
  3. Logging pipeline failures for forensic analysis
  4. Alerting strategies that meet response time goals
  5. Incident classification and escalation paths
  6. Documenting root cause analysis for auditors
  7. Post-mortem templates aligned with ISO 27001
  8. Retention of incident logs and records
  9. Testing response playbooks under ISO standards
  10. Integrating incident data into control reviews
  11. Recovery time objectives and data consistency
  12. Proving resilience through documented rehearsals
Module 9. Third-Party Risk and Vendor Pipeline Integrations
Explore A.15 controls in the context of data pipelines that use third-party APIs, SaaS tools, or managed services. This module shows how to assess and document vendor compliance obligations, especially when data flows through external systems.
12 chapters in this module
  1. Applying A.15.1 to third-party data integrations
  2. Assessing vendor compliance posture for data handling
  3. Documenting data flow through external APIs
  4. Contractual obligations for encryption and access
  5. Audit rights and evidence sharing with vendors
  6. Monitoring third-party service incidents
  7. Data sovereignty risks in SaaS integrations
  8. Building vendor review checklists
  9. Handling sub-processors in data pipelines
  10. Extending control assertions to vendor dependencies
  11. Creating a vendor risk scoring model
  12. Designing fallbacks for critical third-party dependencies
Module 10. Business Continuity and Data Pipeline Recovery
Cover A.17 controls as they apply to data engineers, especially how pipeline architecture supports recovery objectives. This module teaches how to document RTOs, RPOs, and testing outcomes so they satisfy auditor scrutiny.
12 chapters in this module
  1. Defining RTO and RPO for data pipelines
  2. Replication strategies across AWS regions
  3. Backup and restore processes for pipeline state
  4. Documenting recovery procedures for auditors
  5. Testing pipeline recovery under real conditions
  6. Logging recovery test outcomes
  7. Aligning recovery design with data classification
  8. Using S3 cross-region replication
  9. Failover automation in ETL workflows
  10. Proving continuity without live disruption
  11. Retention of recovery test documentation
  12. Integrating disaster recovery with pipeline CI/CD
Module 11. Building the Statement of Applicability (SoA)
Learn how to author a compelling SoA that reflects actual pipeline design decisions. This module walks through clause justification, evidence mapping, and risk-based exemptions. You’ll draft a section of a working SoA using real AWS configurations.
12 chapters in this module
  1. Purpose and structure of the Statement of Applicability
  2. Justifying inclusion or exclusion of controls
  3. Linking pipeline design to control applicability
  4. Documenting risk assessments for exceptions
  5. Using AWS service configurations in justifications
  6. Aligning SoA with auditor expectations
  7. Common gaps in engineer-authored SoAs
  8. Versioning and change tracking for the SoA
  9. Collaborating with security teams on final wording
  10. Building a living SoA updated with pipeline changes
  11. Presenting SoA logic during auditor interviews
  12. Integrating SoA updates into deployment cycles
Module 12. From Knowledge to Field Application
Apply all prior modules to a real-world scenario: an AWS-hosted data pipeline audit. This capstone walks through evidence assembly, SoA alignment, and mock auditor Q&A. You’ll leave with a personal playbook ready for immediate use.
12 chapters in this module
  1. Integrating control mapping across all modules
  2. Building a personal implementation playbook
  3. Assembling evidence for a full audit cycle
  4. Anticipating auditor follow-up questions
  5. Responding to gaps with design logic
  6. Updating the SoA with new pipeline changes
  7. Automating evidence refresh for renewals
  8. Handing off compliance knowledge to new hires
  9. Surviving auditor interviews with confidence
  10. Scaling compliance across multiple pipelines
  11. Maintaining command as frameworks evolve
  12. Leveraging mastery for leadership visibility

How this maps to your situation

  • AWS-hosted data pipelines under ISO 27001
  • Engineer-led compliance in service organizations
  • Audit evidence as code
  • Long-term maintainability of compliance design

Before vs. after

Before
Compliance work feels reactive, evidence gathered last minute, control mappings unclear, auditor questions unpredictable.
After
Design pipelines with control mastery from day one, produce evidence on demand, and lead with confidence in audit cycles.

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 six weeks, with self-paced access to all materials.

If nothing changes
Without deep command of ISO 27001, data engineers risk being sidelined in architecture decisions, over-relying on security teams, and facing repeated audit delays or findings.

How this compares to the alternatives

Generic ISO 27001 courses focus on policy or checklists. This course is built for data engineers who design and run AWS pipelines, teaching control mastery through engineering decisions.

Frequently asked

How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Is this relevant for someone not in security or compliance?
Yes, this course is designed for data engineers who own pipeline design and want full command of how their work maps to ISO 27001.
Do I need AWS admin privileges to benefit?
No, you’ll learn to design and document with control mastery, regardless of access level.
$199 one-time. 90 minutes per week over six weeks, with self-paced access to all materials..

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
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