A tailored course, built for your situation
Mastering AWS Well-Architected for Data Engineering Leaders
Build systems that meet security, cost, and scale benchmarks without senior review cycles
$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
Senior data engineering leader operating in multi-cloud environments with responsibility for system architecture and cross-platform governance
Who this is not for
Junior engineers, platform admins, or teams without decision-making scope over cloud architecture standards
What you walk away with
- Define and enforce architecture review thresholds without escalation
- Own cloud workload placement decisions across AWS and non-AWS environments
- Produce repeatable assessment reports that align security, cost, and operational requirements
- Lead cross-functional design reviews using standardized well-architected checklists
- Make binding decisions on refactoring, modernization, and technical debt resolution paths
The 12 modules (with all 144 chapters)
Module 1. Understanding the AWS Well-Architected Framework
Break down the five pillars: operational excellence, security, reliability, performance efficiency, and cost optimization. Learn how each applies to data-intensive systems in hybrid cloud.
12 chapters in this module
- Origins of the framework
- Pillar 1 overview: operational excellence
- Pillar 2: security baseline
- Pillar 3: reliability expectations
- Pillar 4: performance efficiency
- Pillar 5: cost optimization
- Workload classification types
- Review frequency standards
- Integration with CI/CD pipelines
- Documentation standards
- Tooling ecosystem
- Benchmark scoring methods
Module 2. Applying the Framework to Data Engineering Workloads
Map core data patterns , batch ETL, streaming, ELT, feature stores , to relevant architectural concerns and risk thresholds.
12 chapters in this module
- ETL pipeline assessment
- Streaming architecture review
- Data lakehouse alignment
- Governance layer integration
- Metadata management scope
- Access control mapping
- Cross-account data sharing
- Encryption in transit and at rest
- Resource provisioning controls
- Auto-scaling boundaries
- SLO definitions for pipelines
- Failure recovery testing
Module 3. Conducting a Well-Architected Review
Walk through conducting a full review: from scheduling to follow-up tracking, with emphasis on data system specifics.
12 chapters in this module
- Preparing for the review
- Stakeholder identification
- Baseline gathering techniques
- Workload inventory documentation
- Performance baseline capture
- Cost anomaly detection
- Security configuration audit
- Reliability testing scope
- Operational procedure check
- Finding severity grading
- Remediation roadmap creation
- Tracking closure progress
Module 4. Security Pillar Deep Dive
Focus on identity, encryption, network controls, and data protection in multi-cloud data architectures.
12 chapters in this module
- IAM role design patterns
- Cross-account access risks
- Principle of least privilege
- Encryption key lifecycle
- Data masking requirements
- Network segmentation models
- VPC peering security
- PrivateLink usage
- Data exfiltration controls
- Audit log completeness
- Threat detection integration
- Incident response alignment
Module 5. Reliability in Data Systems
Ensure data pipelines and storage layers can recover from disruptions without data loss or extended downtime.
12 chapters in this module
- Data pipeline redundancy
- Checkpointing mechanisms
- Idempotency design
- Backup frequency standards
- Cross-region replication
- Failover testing cadence
- Data integrity validation
- Disaster recovery runbooks
- Automated failover triggers
- Monitoring coverage scope
- Chaos engineering basics
- Recovery time objectives
Module 6. Cost Optimization for Data Platforms
Identify and act on wasteful spending in storage, compute, and network transfer without sacrificing performance.
12 chapters in this module
- Storage tiering strategy
- Query cost analysis
- Compute auto-scaling rules
- Spot instance usage
- Unattached resource cleanup
- Data lifecycle policies
- Query optimization levers
- Caching layer impact
- Data duplication costs
- Cross-cloud egress fees
- Reserved instance planning
- Cost allocation tagging
Module 7. Performance Efficiency in Practice
Tune data systems for speed and responsiveness while maintaining resource discipline.
12 chapters in this module
- Query execution path analysis
- Partitioning strategies
- Indexing for analytics
- Materialized view management
- Cluster sizing rules
- Concurrency handling
- Pipeline parallelization
- Data format selection
- Compression trade-offs
- Network throughput limits
- Latency SLA tracking
- Load testing methodology
Module 8. Operational Excellence for Data Teams
Implement practices that keep systems observable, maintainable, and aligned with business needs.
12 chapters in this module
- Incident response workflow
- Runbook documentation
- Change management process
- Monitoring coverage
- Alert fatigue reduction
- Post-mortem standards
- Automated remediation
- Drift detection systems
- Capacity planning rhythm
- Feedback loop integration
- Tooling standardization
- Team onboarding process
Module 9. Cross-Cloud Architecture Decisions
Apply well-architected principles when integrating AWS with Azure and other platforms.
12 chapters in this module
- Data transfer protocols
- Identity federation models
- Consistent policy enforcement
- Monitoring unification
- Cost attribution models
- SLA alignment across clouds
- Data sovereignty constraints
- Hybrid key management
- Latency-aware routing
- Multi-cloud observability
- Vendor lock-in mitigation
- Exit strategy documentation
Module 10. Building Reusable Review Artifacts
Create templates, scorecards, and checklists that persist beyond individual reviews.
12 chapters in this module
- Custom question library
- Automated finding generation
- Scoring rubric design
- Report formatting standards
- Stakeholder-specific views
- Executive summary creation
- Technical detail appendices
- Version control integration
- Template reuse workflow
- Peer review process
- Audit readiness updates
- Training material derivation
Module 11. Influencing Without Authority
Lead change across teams that operate outside direct reporting lines using data and framework alignment.
12 chapters in this module
- Building consensus
- Stakeholder mapping
- Data-driven persuasion
- Framework as common language
- Escalation avoidance
- Peer review engagement
- Change adoption metrics
- Success story documentation
- Executive sponsorship
- Feedback integration
- Iteration planning
- Progress visibility
Module 12. Sustaining Architectural Standards
Turn one-time reviews into ongoing governance that survives team changes and platform evolution.
12 chapters in this module
- Review cadence definition
- Onboarding new workloads
- Architecture runway planning
- Technical debt tracking
- Policy exception process
- Standards evolution process
- Leadership engagement rhythm
- Metrics reporting dashboard
- Cross-team alignment
- Framework update absorption
- Lessons learned capture
- Knowledge transfer planning
How this maps to your situation
- New cloud project initiation
- Post-incident architecture review
- Multi-cloud integration planning
- Platform modernization cycle
Before vs. after
Before
Waiting for external validation on architecture choices, repeating reviews, explaining decisions post-hoc
After
Confidently making binding decisions on system design, with documented alignment to industry standards
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: Approximately 3 hours per module, designed to be completed over 4-6 weeks with team application.
If nothing changes
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How this compares to the alternatives
Unlike generic cloud training, this course focuses on real-world decision-making authority and includes field-tested templates used by senior engineering leaders.
Frequently asked
Is this only relevant for AWS environments?
No. The framework is applied to hybrid and multi-cloud data systems, including those anchored in Azure.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Does the course cover Snowflake?
The course focuses on architectural decision-making frameworks applicable across platforms, not specific tool instruction.
$199 one-time. Approximately 3 hours per module, designed to be completed over 4-6 weeks with team application..
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