Architecture Delivery And Communication

Why this skill matters for a Data Architect

Great architectures fail if they aren’t understood, adopted, or safely delivered. Architecture Delivery and Communication turns designs into outcomes: clear diagrams and RFCs, consistent standards, effective reviews and governance, phased migrations, explicit risk tradeoffs, crisp cross-team collaboration, auditable decision logs, and enablement that helps teams ship confidently.

Who this is for

• Data Architects defining platform and domain data solutions.
• Senior Data/Platform Engineers leading cross-team initiatives.
• Technical Leads preparing for governance boards or large migrations.

Prerequisites

• Working knowledge of data platforms (e.g., warehouses, lakehouses, streaming).
• Familiarity with core data modeling, pipelines, and infrastructure-as-code.
• Basic security, reliability, and cost concepts in cloud environments.

Learning path

Worked examples

Example 1: Architecture diagram + RFC snippet

Use layered views: context (who/why), container (systems), and component (key internals). Keep labels actionable.

Context: BI Analysts, ML Team, Data Platform

Diagram (text view):
[Prod DB] --CDC--> [Kafka] --stream--> [Stream Processor] --sink--> [Feature Store]
[Stream Processor] --batch--> [Data Lake] --ELT--> [Warehouse]
[Warehouse] --BI--> [Dashboards]

RFC Title: Real-time Features for Recommendations
Summary: Introduce CDC to stream product updates into a feature store with 1–2 min latency.
Scope: Product catalog, pricing. Non-goals: Historical backfill for 3+ years.
Success Metrics: p95 latency < 120s, data freshness alerts < 0.5% monthly.
Assumptions: Kafka available, existing observability stack.

Example 2: Standards + reference implementation

Standards should be short, testable, and tied to a reference implementation that teams can copy.

Naming Standard (Kafka):
<domain>.<entity>.<event>.v<major>
Examples: catalog.product.upsert.v1, pricing.discount.applied.v2

Schema Standard:
- Backward-compatible Avro schemas
- Envelope: { event_id, event_time, source, payload }

Reference Terraform (snippet):
module "kafka_topic_catalog_product_upsert_v1" {
  source  = "modules/kafka-topic"
  name    = "catalog.product.upsert.v1"
  config  = { partitions = 6, replication_factor = 3 }
  tags    = { owner = "catalog-team", pii = "none" }
}

Example 3: Design review/governance packet

Frame the conversation around risks and choices, not just the happy path.

Example 4: Migration plan and phased rollout

Use canaries and parallel runs before cutover. Plan a rollback that is as simple as a switch.

Phases:
1) Shadow: Produce new topic, do not consume to prod features
2) Parallel run: Compare aggregates in lake vs. warehouse (24–72h)
3) Canary: 5% traffic reads from new feature store
4) Cutover: 100% traffic; keep old path hot for 24h
5) Cleanup: Decommission old path after 7 days of stability

Canary config (pseudo):
FEATURE_STORE_ROLLOUT_PERCENT=5

Rollback:
- Set FEATURE_STORE_ROLLOUT_PERCENT=0
- Pause consumers on new topic
- Revert traffic to warehouse features

Example 5: Risk assessment and tradeoffs

Make risks explicit and pair each with a mitigation and owner.

Risk: Schema drift breaks consumers
Impact: High | Likelihood: Medium
Mitigation: Schema registry with compatibility=BACKWARD; contract tests in CI
Owner: Data Platform team

Risk: Cost spike in streaming storage
Impact: Medium | Likelihood: Medium
Mitigation: Retention 72h, tiered storage, cost alerts
Owner: FinOps + Platform

Tradeoff: Lambda vs. Medallion
- Lambda: lower latency, higher complexity
- Medallion: simpler governance, slightly higher latency
Decision: Medallion; latency target still met (<120s)

Example 6: Decision log (ADR)

ADR-014 Use Avro with Backward Compatibility for Events
Status: Accepted (2026-01-10)
Context: Multiple teams publishing events; schema drift incidents observed.
Decision: Adopt Avro + Schema Registry with BACKWARD compatibility.
Consequences: Safe evolution; producers must only add optional fields.
Alternatives: JSON (no registry), Protobuf (higher friction for teams today).

Drills and exercises

• Draft a one-page RFC for a new dataset, including non-goals and KPIs.
• Redraw an existing diagram to separate context, container, and component views.
• Create a naming standard for 5 datasets and a matching validation checklist.
• Write a two-phase migration plan with a measurable canary step.
• List top 5 risks for your platform; add mitigations and owners.
• Write an ADR for a storage format choice and share it with your team.

Common mistakes and debugging tips

• Mistake: Diagrams too detailed for execs or too high-level for engineers. Tip: Provide multiple views (context, container, component).
• Mistake: No measurable success criteria. Tip: Add 2–3 KPIs with baselines and targets.
• Mistake: Big-bang migrations. Tip: Use shadow, parallel run, and canary with rollback toggles.
• Mistake: Vague “we’ll monitor it.” Tip: Define alerts and thresholds per SLO (e.g., p95 < 120s).
• Mistake: Decisions lost in chats. Tip: Use ADRs with IDs and dates; link from RFCs.
• Mistake: Governance as a gate, not guidance. Tip: Engage reviewers early with a pre-read.

Practical projects

• Publish a reference ingestion pipeline (batch and streaming) with templates and a 10-minute quickstart.
• Standardize event naming and schema evolution; add CI checks to block non-compliant changes.
• Run a mock design review: share pre-read, collect decisions, and post a summary with action items.

Mini project: Ship a standards-backed feature pipeline

Subskills

• Architecture Diagrams And RFCs: Communicate intent with layered visuals and concise specs.
• Standards And Reference Implementations: Make the right path the easy path.
• Design Reviews And Governance Boards: Secure alignment and de-risk decisions.
• Migration Planning And Phased Rollouts: Deliver safely with canaries and rollbacks.
• Risk Management And Tradeoffs: Surface choices with clear consequences.
• Cross Team Collaboration: Align roles, timelines, and shared outcomes.
• Decision Logs: Keep an auditable record of why the team chose an approach.
• Mentoring And Enablement: Uplevel teams so the architecture sticks.

Next steps

• Pick one active initiative and apply this flow: RFC → review → canary → cutover.
• Schedule a 45-minute enablement session; record it and share the deck and checklist.
• Keep a lightweight decision log in your repo; review it quarterly for consistency.

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