Data Architecture
Data Architecture is an individual-contributor Data + AI career progressing from guided delivery to enterprise expertise without requiring people management.
- Function
- Data & Analytics
- Archetype
- Architecture
- Highest level
- L7 · Distinguished Data Architect
Why it exists
Defines enterprise data architecture, models, integration patterns, platform boundaries and governance principles for scalable trusted data products.
Typical responsibilities
Deliver data architecture outcomes; apply data/AI standards; manage quality, reliability and risk; collaborate across product, engineering, security, legal and business teams; at senior levels shape enterprise standards and strategy.
Where the work happens
Technology companies, data/cloud platforms, financial services, consulting, shared services, product engineering and regulated enterprises adopting Data + AI.
How the career progresses
Associate Data Architect → Data Architect → Senior Data Architect → Staff Data Architect → Principal Data Architect → Senior Principal Data Architect → Distinguished Data Architect
Levels in this career
Six standard stages. The seventh exists only where the career provides for it.
- L1Associate Data Architect
- L2Data Architect
- L3Senior Data Architect
- L4Staff Data Architect
- L5Principal Data Architect
- L6Senior Principal Data Architect
- L7Distinguished Data Architect
Optional distinguished level. Not every career reaches it.
What is expected at L1 · Associate Data Architect
Apply data architecture capability at learns the discipline and executes defined work with guidance.
The five dimensions that change
- Autonomy
- Close guidance
- Scope
- Learns the discipline and executes defined work with guidance.
- Complexity
- Defined
- Influence
- Immediate team
- Business impact
- Task/team
- Ambiguity
- Low
What good looks like
Produces trustworthy data architecture outcomes, makes sound trade-offs, communicates evidence and risks, and demonstrates the autonomy and impact expected at L1.
Typical evidence
Completed data architecture work products or production outcomes; documented decisions; measurable improvements in quality, reliability, risk, speed, cost or business outcomes; peer/stakeholder evidence of L1 scope.
Skills expected at L1
Grouped as human, professional and technical. Target proficiency uses the P1–P7 scale, and each row says what that level means for that particular skill.
Human6
| Human | P | Supporting |
|---|---|---|
| Clear verbal communicationCommunication & Language | P1AwarenessSupporting | Understands the purpose, vocabulary and basic principles of Clear verbal communication; works with close guidance. |
| Clear written communicationCommunication & Language | P1AwarenessSupporting | Understands the purpose, vocabulary and basic principles of Clear written communication; works with close guidance. |
| CollaborationCollaboration & Relationships | P1AwarenessSupporting | Understands the purpose, vocabulary and basic principles of Collaboration; works with close guidance. |
| Critical thinkingThinking & Problem Solving | P1AwarenessSupporting | Understands the purpose, vocabulary and basic principles of Critical thinking; works with close guidance. |
| Cross-functional collaborationCollaboration & Relationships | P1AwarenessSupporting | Understands the purpose, vocabulary and basic principles of Cross-functional collaboration; works with close guidance. |
| Structured problem solvingThinking & Problem Solving | P1AwarenessSupporting | Understands the purpose, vocabulary and basic principles of Structured problem solving; works with close guidance. |
Professional6
| Professional | P | Supporting |
|---|---|---|
| Architecture governanceIT Service Management & Governance | P1AwarenessSupporting | Understands the purpose, vocabulary and basic principles of Architecture governance; works with close guidance. |
| Data governanceCybersecurity, Privacy & Data Governance Standards | P1AwarenessCore | Understands the purpose, vocabulary and basic principles of Data governance; works with close guidance. |
| Data product managementData & Analytics Practice | P1AwarenessSupporting | Understands the purpose, vocabulary and basic principles of Data product management; works with close guidance. |
| Data quality managementCybersecurity, Privacy & Data Governance Standards | P1AwarenessCore | Understands the purpose, vocabulary and basic principles of Data quality management; works with close guidance. |
| Data stewardshipCybersecurity, Privacy & Data Governance Standards | P1AwarenessCore | Understands the purpose, vocabulary and basic principles of Data stewardship; works with close guidance. |
| Technology governanceIT Service Management & Governance | P1AwarenessSupporting | Understands the purpose, vocabulary and basic principles of Technology governance; works with close guidance. |
Technical8
| Technical | P | Supporting |
|---|---|---|
| Data catalog platformsDatabases & Data Platforms | P1AwarenessSupporting | Recognizes the purpose, core concepts and risks of Data catalog platforms; performs only guided exercises. |
| Data lake / lakehouse engineeringDatabases & Data Platforms | P1AwarenessCore | Recognizes the purpose, core concepts and risks of Data lake / lakehouse engineering; performs only guided exercises. |
| Data lineage toolingDatabases & Data Platforms | P1AwarenessSupporting | Recognizes the purpose, core concepts and risks of Data lineage tooling; performs only guided exercises. |
| Data mesh architectureDatabases & Data Platforms | P1AwarenessSupporting | Recognizes the purpose, core concepts and risks of Data mesh architecture; performs only guided exercises. |
| Data modelingDatabases & Data Platforms | P1AwarenessCore | Recognizes the purpose, core concepts and risks of Data modeling; performs only guided exercises. |
| Data warehouse engineeringDatabases & Data Platforms | P1AwarenessCore | Recognizes the purpose, core concepts and risks of Data warehouse engineering; performs only guided exercises. |
| ER modelingArchitecture & Modeling Tools | P1AwarenessCore | Recognizes the purpose, core concepts and risks of ER modeling; performs only guided exercises. |
| Semantic layer engineeringAnalytics, BI & Data Visualization | P1AwarenessSupporting | Recognizes the purpose, core concepts and risks of Semantic layer engineering; performs only guided exercises. |
What changes from L1 to L2
Moving from Associate Data Architect to Data Architect means greater autonomy, complexity, scope, influence and evidence of impact—not simply more tools.
How readiness is shown
Sustained evidence of operating at L2-type scope: handles representative complexity, influences expected stakeholders and produces durable measurable outcomes.
How to prepare
Take on one assignment at next-level scope; seek feedback; document decisions/outcomes; mentor others where appropriate; close highest-priority skill gaps.
Adjacent careers
Computed from shared skills. It is a signal for exploring, not a hiring or eligibility guarantee.
- Analytics EngineeringData & Analytics21 shared skills
- AI Platform & MLOps EngineeringData & Analytics14 shared skills
- Data EngineeringData & Analytics15 shared skills
- AI Governance & Responsible AIData & Analytics12 shared skills
- Data AnalyticsData & Analytics15 shared skills
- Business IntelligenceData & Analytics15 shared skills
Career framework v21, active since August 17, 2026.