Analytics Engineering
Analytics Engineering is an individual-contributor Data + AI career progressing from guided delivery to enterprise expertise without requiring people management.
- Función
- Data & Analytics
- Arquetipo
- Engineering
- Nivel más alto
- L6 · Principal Analytics Engineer
Para qué existe
Transforms modeled data into governed analytical datasets, semantic models and trusted metrics for self-service analytics.
Responsabilidades típicas
Deliver analytics engineering 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 Analytics Engineer → Analytics Engineer → Senior Analytics Engineer → Staff Analytics Engineer → Senior Staff Analytics Engineer → Principal Analytics Engineer
Niveles de esta carrera
Seis etapas estándar. La séptima existe solo donde la carrera la contempla.
Qué se espera en L1 · Associate Analytics Engineer
Apply analytics engineering capability at learns the discipline and executes defined work with guidance.
Las cinco dimensiones que cambian
- Autonomía
- Close guidance
- Alcance
- Learns the discipline and executes defined work with guidance.
- Complejidad
- Defined
- Influencia
- Immediate team
- Impacto en el negocio
- Task/team
- Ambigüedad
- Low
Cómo se ve un buen desempeño
Produces trustworthy analytics engineering outcomes, makes sound trade-offs, communicates evidence and risks, and demonstrates the autonomy and impact expected at L1.
Evidencia típica
Completed analytics engineering work products or production outcomes; documented decisions; measurable improvements in quality, reliability, risk, speed, cost or business outcomes; peer/stakeholder evidence of L1 scope.
Habilidades esperadas en L1
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.
Humanas6
| Humanas | P | De apoyo |
|---|---|---|
| Clear verbal communicationCommunication & Language | P1AwarenessDe apoyo | Understands the purpose, vocabulary and basic principles of Clear verbal communication; works with close guidance. |
| Clear written communicationCommunication & Language | P1AwarenessDe apoyo | Understands the purpose, vocabulary and basic principles of Clear written communication; works with close guidance. |
| CollaborationCollaboration & Relationships | P1AwarenessDe apoyo | Understands the purpose, vocabulary and basic principles of Collaboration; works with close guidance. |
| Critical thinkingThinking & Problem Solving | P1AwarenessDe apoyo | Understands the purpose, vocabulary and basic principles of Critical thinking; works with close guidance. |
| Cross-functional collaborationCollaboration & Relationships | P1AwarenessDe apoyo | Understands the purpose, vocabulary and basic principles of Cross-functional collaboration; works with close guidance. |
| Structured problem solvingThinking & Problem Solving | P1AwarenessDe apoyo | Understands the purpose, vocabulary and basic principles of Structured problem solving; works with close guidance. |
Profesionales6
| Profesionales | P | De apoyo |
|---|---|---|
| Analytics problem framingData & Analytics Practice | P1AwarenessCentral | Understands the purpose, vocabulary and basic principles of Analytics problem framing; works with close guidance. |
| Data governanceCybersecurity, Privacy & Data Governance Standards | P1AwarenessDe apoyo | Understands the purpose, vocabulary and basic principles of Data governance; works with close guidance. |
| Data product managementData & Analytics Practice | P1AwarenessDe apoyo | Understands the purpose, vocabulary and basic principles of Data product management; works with close guidance. |
| Data quality managementCybersecurity, Privacy & Data Governance Standards | P1AwarenessDe apoyo | Understands the purpose, vocabulary and basic principles of Data quality management; works with close guidance. |
| KPI designData & Analytics Practice | P1AwarenessCentral | Understands the purpose, vocabulary and basic principles of KPI design; works with close guidance. |
| Metrics definitionData & Analytics Practice | P1AwarenessCentral | Understands the purpose, vocabulary and basic principles of Metrics definition; works with close guidance. |
Técnicas8
| Técnicas | P | De apoyo |
|---|---|---|
| Dashboard developmentAnalytics, BI & Data Visualization | P1AwarenessDe apoyo | Recognizes the purpose, core concepts and risks of Dashboard development; performs only guided exercises. |
| Data lineage toolingDatabases & Data Platforms | P1AwarenessDe apoyo | Recognizes the purpose, core concepts and risks of Data lineage tooling; performs only guided exercises. |
| Data modelingDatabases & Data Platforms | P1AwarenessCentral | Recognizes the purpose, core concepts and risks of Data modeling; performs only guided exercises. |
| Data visualization implementationAnalytics, BI & Data Visualization | P1AwarenessDe apoyo | Recognizes the purpose, core concepts and risks of Data visualization implementation; performs only guided exercises. |
| Dimensional modelingDatabases & Data Platforms | P1AwarenessCentral | Recognizes the purpose, core concepts and risks of Dimensional modeling; performs only guided exercises. |
| SQL analyticsAnalytics, BI & Data Visualization | P1AwarenessCentral | Recognizes the purpose, core concepts and risks of SQL analytics; performs only guided exercises. |
| Semantic layer engineeringAnalytics, BI & Data Visualization | P1AwarenessDe apoyo | Recognizes the purpose, core concepts and risks of Semantic layer engineering; performs only guided exercises. |
| dbtDatabases & Data Platforms | P1AwarenessCentral | Recognizes the purpose, core concepts and risks of dbt; performs only guided exercises. |
Qué cambia al pasar de L1 a L2
Moving from Associate Analytics Engineer to Analytics Engineer 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 L2-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.
- Data ArchitectureData & Analytics21 habilidades compartidas
- AI Governance & Responsible AIData & Analytics12 habilidades compartidas
- AI Platform & MLOps EngineeringData & Analytics12 habilidades compartidas
- Data AnalyticsData & Analytics15 habilidades compartidas
- Business IntelligenceData & Analytics15 habilidades compartidas
- Data EngineeringData & Analytics15 habilidades compartidas
Marco de carreras v21, activo desde 17 de agosto de 2026.