A tailored course, built for your situation
Faster Path from Intent to Working AWS Well-Architected Implementation
Ship compliant, high-performance cloud data systems faster using AWS Well-Architected as your guide
$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.
Spending too long in review cycles, audit prep, and rework because architecture decisions weren't validated early enough
The situation this course is for
Engineers ship code fast, but then get stuck in compliance reviews, stakeholder revisions, or security findings that require major rework. The root cause? Architecture decisions made in isolation from established guardrails. The cost is velocity, and credibility.
Who this is for
Senior data engineer or cloud data practitioner shipping analytics, ETL, and data products on AWS and Snowflake, who needs to move fast without breaking governance or performance standards
Who this is not for
Entry-level analysts, non-technical compliance staff, or cloud generalists not actively shipping data pipelines with DBT and SQL on AWS
What you walk away with
- Proactively align data architecture decisions with AWS Well-Architected pillars before implementation begins
- Reduce audit remediation time by embedding framework checks into DBT test suites
- Turn compliance requirements into reusable SQL and DBT patterns
- Accelerate stakeholder sign-off with traceable framework mappings
- Deliver working artefacts 30-50% faster by avoiding late-stage rework
The 12 modules (with all 144 chapters)
Module 1. AWS Well-Architected Framework Orientation
Understand the five pillars as applied to data engineering , not theoretical cloud, but real SQL, DBT, and ETL workflows.
12 chapters in this module
- What the framework really enables
- Pillar 1 reliability in ETL contexts
- Pillar 2 performance efficiency
- Pillar 3 security baseline
- Pillar 4 cost optimization
- Pillar 5 operational excellence
- How reviews are scored
- Common misalignments in data layers
- Framework vs internal policies
- Mapping to DBT models
- SQL anti-patterns to avoid
- First review simulation
Module 2. Reliability by Design in Data Pipelines
Embed reliability checks into SQL and DBT so jobs fail fast, recover cleanly, and avoid downstream corruption.
12 chapters in this module
- Idempotent ETL patterns
- Primary key validation
- Backfill safety
- Dependency tracking
- Retry logic in Airflow
- Schema drift detection
- Data freshness guards
- DBT tests for nulls
- Windowing edge cases
- Merge vs insert
- Checkpointing in stages
- Error budget for pipelines
Module 3. Performance Efficiency in Query Design
Write SQL that scales , using framework principles to avoid bottlenecks before they emerge.
12 chapters in this module
- Cluster key selection
- Partition pruning
- Join order optimization
- CTE misuse patterns
- Materialized view criteria
- Query plan reading
- Cost per query tracking
- Indexing alternatives
- Predicate pushdown
- Result set sizing
- Caching strategies
- Workload isolation
Module 4. Security First in Data Architecture
Implement least privilege, encryption, and audit trails as standard , not after a finding.
12 chapters in this module
- Column-level masking
- Role hierarchy design
- Temporary credential flow
- Audit log retention
- Data lineage tagging
- PII detection in DBT
- Row access policies
- Secure UDF patterns
- Cross-account access
- S3 bucket policies
- KMS key management
- Secret rotation in CI
Module 5. Cost Optimization Across Data Workflows
Avoid overprovisioning and silent waste , tune compute, storage, and concurrency using framework benchmarks.
12 chapters in this module
- Warehouse sizing rules
- Auto-suspend timing
- Query throttling
- Storage tier selection
- Zero-copy cloning use cases
- Data retention policies
- Concurrency monitoring
- Budget alerts
- S3 lifecycle rules
- DBT run cost tracking
- Spot instance risks
- Cross-region transfer
Module 6. Operational Excellence in CI/CD
Treat data pipelines like software , with versioned, tested, and deployable changes.
12 chapters in this module
- DBT CI pipeline
- Git branching model
- PR checklist
- Test coverage minimum
- Deployment windows
- Rollback strategy
- Monitoring integration
- Alert threshold setting
- Schema change comms
- Uptime SLA tracking
- Incident runbook
- Blameless postmortem
Module 7. Automating Framework Reviews
Turn manual checklists into automated tests , so compliance moves at engineering speed.
12 chapters in this module
- Framework to checklist map
- Control tagging
- Automated evidence capture
- DBT test for controls
- Policy-as-code tools
- Custom rule writing
- Framework score dashboard
- Self-reporting pipelines
- Reviewer handoff
- Evidence retention
- Audit-ready output
- Control drift alerts
Module 8. Cross-Team Alignment Using Framework Language
Use AWS Well-Architected as a shared vocabulary to align data, infra, and security teams.
12 chapters in this module
- Shared review cadence
- Joint scorecards
- Escalation thresholds
- Stakeholder summaries
- Control ownership
- RACI for data layers
- Arch board prep
- Vendor integration
- Onboarding checklist
- Training materials
- Roadmap alignment
- Feedback loops
Module 9. Fast-Tracking New Projects
Start new data initiatives with embedded framework alignment , so you ship faster, not slower.
12 chapters in this module
- Template project setup
- Baseline config stack
- Framework-first design
- Kickoff checklist
- Pilot scope
- Stakeholder map
- Control inventory
- Risk register
- Early validation
- Milestone plan
- Sign-off criteria
- Post-launch review
Module 10. Scaling Patterns Across Teams
Turn one team's success into repeatable patterns , so others ship faster without reinventing.
12 chapters in this module
- Pattern library
- Shared macros
- DBT package use
- Style guide
- Peer review process
- Guild model
- Champion network
- Training rollout
- Feedback capture
- Version governance
- Adoption tracking
- Performance benchmark
Module 11. Handling Major Changes and Migrations
Apply the framework during schema changes, warehouse migrations, and platform upgrades , without slowing down.
12 chapters in this module
- Change impact scope
- Backward compatibility
- Cut-over plan
- Data validation
- Performance baseline
- Fallback strategy
- User comms
- Monitoring ramp-up
- Control revalidation
- Cost reforecast
- Post-migration review
- Lessons documented
Module 12. Sustaining Velocity Over Time
Keep the momentum , evolving your framework alignment as systems and teams grow.
12 chapters in this module
- Review cycle cadence
- Tech debt tracking
- Control update process
- Framework versioning
- Team onboarding
- Metrics reporting
- Improvement backlog
- External audit prep
- Lessons sharing
- Tooling upgrades
- Benchmarking
- Certification prep
How this maps to your situation
- Starting a new data project
- Facing compliance review
- Scaling team delivery
- Migrating existing systems
Before vs. after
Before
Architecture reviews happen late. Compliance findings cause rework. Stakeholders delay sign-off. Velocity stalls.
After
Framework alignment starts early. Controls are embedded. Artefacts pass audit cleanly. Work moves faster from intent to production.
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 3-4 hours per module, designed to be consumed alongside active projects.
If nothing changes
Teams that don't operationalize AWS Well-Architected at engineering speed will continue to ship fast , but get slowed down at review, audit, and scale. The cost is rework, credibility, and missed opportunities to lead.
How this compares to the alternatives
Generic AWS training teaches cloud services. This course teaches how to ship compliant, high-velocity data work using the AWS Well-Architected Framework , specifically for engineers using SQL, DBT, and Snowflake on AWS.
Frequently asked
Is this course about AWS or Snowflake?
It's about using the AWS Well-Architected Framework to improve data engineering outcomes , regardless of where data is stored. You'll learn how to apply the framework to pipelines that use both AWS and Snowflake.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Will this help me pass an AWS certification?
The course focuses on practical implementation, not exam prep , though it deeply reinforces concepts tested in AWS certifications.
$199 one-time. Approximately 3-4 hours per module, designed to be consumed alongside active projects..
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