Data Architecture
Data Architecture is an individual-contributor Data + AI career progressing from guided delivery to enterprise expertise without requiring people management.
- Función
- Data & Analytics
- Arquetipo
- Architecture
- Nivel más alto
- L7 · Distinguished Data Architect
Para qué existe
Defines enterprise data architecture, models, integration patterns, platform boundaries and governance principles for scalable trusted data products.
Responsabilidades típicas
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.
Dónde se trabaja
Technology companies, data/cloud platforms, financial services, consulting, shared services, product engineering and regulated enterprises adopting Data + AI.
Cómo avanza la carrera
Associate Data Architect → Data Architect → Senior Data Architect → Staff Data Architect → Principal Data Architect → Senior Principal Data Architect → Distinguished Data Architect
Niveles de esta carrera
Seis etapas estándar. La séptima existe solo donde la carrera la contempla.
- L1Associate Data Architect
- L2Data Architect
- L3Senior Data Architect
- L4Staff Data Architect
- L5Principal Data Architect
- L6Senior Principal Data Architect
- L7Distinguished Data Architect
Nivel distinguido opcional. No todas las carreras llegan acá.
Qué se espera en L2 · Data Architect
Apply data architecture capability at independently delivers standard work within a team or defined domain.
Las cinco dimensiones que cambian
- Autonomía
- Independent routine ownership
- Alcance
- Independently delivers standard work within a team or defined domain.
- Complejidad
- Moderate
- Influencia
- Immediate team
- Impacto en el negocio
- Task/team
- Ambigüedad
- Moderate
Cómo se ve un buen desempeño
Produces trustworthy data architecture outcomes, makes sound trade-offs, communicates evidence and risks, and demonstrates the autonomy and impact expected at L2.
Evidencia típica
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 L2 scope.
Habilidades esperadas en L2
Agrupadas en humanas, profesionales y técnicas. La proficiencia meta usa la escala P1–P7, y cada fila dice qué significa ese nivel para esa habilidad.
Humanas8
| Humanas | P | De apoyo |
|---|---|---|
| Clear verbal communicationCommunication & Language | P2FoundationalDe apoyo | Applies Clear verbal communication to routine situations using established methods and controls. |
| Clear written communicationCommunication & Language | P2FoundationalDe apoyo | Applies Clear written communication to routine situations using established methods and controls. |
| CollaborationCollaboration & Relationships | P2FoundationalDe apoyo | Applies Collaboration to routine situations using established methods and controls. |
| Critical thinkingThinking & Problem Solving | P2FoundationalDe apoyo | Applies Critical thinking to routine situations using established methods and controls. |
| Cross-functional collaborationCollaboration & Relationships | P2FoundationalDe apoyo | Applies Cross-functional collaboration to routine situations using established methods and controls. |
| Learning agilityExecution & Self-Management | P2FoundationalDe apoyo | Applies Learning agility to routine situations using established methods and controls. |
| Stakeholder alignmentInfluence & Leadership Without Authority | P2FoundationalDe apoyo | Applies Stakeholder alignment to routine situations using established methods and controls. |
| Structured problem solvingThinking & Problem Solving | P2FoundationalDe apoyo | Applies Structured problem solving to routine situations using established methods and controls. |
Profesionales7
| Profesionales | P | De apoyo |
|---|---|---|
| Architecture governanceIT Service Management & Governance | P2FoundationalDe apoyo | Applies Architecture governance to routine situations using established methods and controls. |
| Data governanceCybersecurity, Privacy & Data Governance Standards | P2FoundationalCentral | Applies Data governance to routine situations using established methods and controls. |
| Data mesh operating modelData & Analytics Practice | P2FoundationalDe apoyo | Applies Data mesh operating model to routine situations using established methods and controls. |
| Data product managementData & Analytics Practice | P2FoundationalDe apoyo | Applies Data product management to routine situations using established methods and controls. |
| Data quality managementCybersecurity, Privacy & Data Governance Standards | P2FoundationalCentral | Applies Data quality management to routine situations using established methods and controls. |
| Data stewardshipCybersecurity, Privacy & Data Governance Standards | P2FoundationalCentral | Applies Data stewardship to routine situations using established methods and controls. |
| Technology governanceIT Service Management & Governance | P2FoundationalDe apoyo | Applies Technology governance to routine situations using established methods and controls. |
Técnicas10
| Técnicas | P | De apoyo |
|---|---|---|
| Apache KafkaDatabases & Data Platforms | P2FoundationalDe apoyo | Uses Apache Kafka for routine tasks with documented patterns and review. |
| Data catalog platformsDatabases & Data Platforms | P2FoundationalDe apoyo | Uses Data catalog platforms for routine tasks with documented patterns and review. |
| Data contract implementationDatabases & Data Platforms | P2FoundationalDe apoyo | Uses Data contract implementation for routine tasks with documented patterns and review. |
| Data lake / lakehouse engineeringDatabases & Data Platforms | P2FoundationalCentral | Uses Data lake / lakehouse engineering for routine tasks with documented patterns and review. |
| Data lineage toolingDatabases & Data Platforms | P2FoundationalDe apoyo | Uses Data lineage tooling for routine tasks with documented patterns and review. |
| Data mesh architectureDatabases & Data Platforms | P2FoundationalCentral | Uses Data mesh architecture for routine tasks with documented patterns and review. |
| Data modelingDatabases & Data Platforms | P2FoundationalCentral | Uses Data modeling for routine tasks with documented patterns and review. |
| Data warehouse engineeringDatabases & Data Platforms | P2FoundationalCentral | Uses Data warehouse engineering for routine tasks with documented patterns and review. |
| ER modelingArchitecture & Modeling Tools | P2FoundationalCentral | Uses ER modeling for routine tasks with documented patterns and review. |
| Semantic layer engineeringAnalytics, BI & Data Visualization | P2FoundationalDe apoyo | Uses Semantic layer engineering for routine tasks with documented patterns and review. |
Qué cambia al pasar de L2 a L3
Moving from Data Architect to Senior Data Architect means greater autonomy, complexity, scope, influence and evidence of impact—not simply more tools.
Cómo se demuestra que ya estás
Sustained evidence of operating at L3-type scope: handles representative complexity, influences expected stakeholders and produces durable measurable outcomes.
Cómo prepararse
Take on one assignment at next-level scope; seek feedback; document decisions/outcomes; mentor others where appropriate; close highest-priority skill gaps.
Carreras cercanas
Calculadas por habilidades compartidas. Es una señal para explorar, no una garantía de contratación ni de elegibilidad.
- Analytics EngineeringData & Analytics21 habilidades compartidas
- AI Platform & MLOps EngineeringData & Analytics14 habilidades compartidas
- Data EngineeringData & Analytics15 habilidades compartidas
- AI Governance & Responsible AIData & Analytics12 habilidades compartidas
- Data AnalyticsData & Analytics15 habilidades compartidas
- Business IntelligenceData & Analytics15 habilidades compartidas
Marco de carreras v21, activo desde 17 de agosto de 2026.