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 L3 · Senior Analytics Engineer
Apply analytics engineering capability at handles complex work, mentors others and influences team-level outcomes.
Las cinco dimensiones que cambian
- Autonomía
- Independent complex ownership
- Alcance
- Handles complex work, mentors others and influences team-level outcomes.
- Complejidad
- Complex
- Influencia
- Multiple teams
- Impacto en el negocio
- Domain/cross-team
- Ambigüedad
- Moderate
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 L3.
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 L3 scope.
Habilidades esperadas en L3
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 | P3WorkingDe apoyo | Applies Clear verbal communication independently in normal and moderately complex situations. |
| Clear written communicationCommunication & Language | P3WorkingDe apoyo | Applies Clear written communication independently in normal and moderately complex situations. |
| CollaborationCollaboration & Relationships | P3WorkingDe apoyo | Applies Collaboration independently in normal and moderately complex situations. |
| Critical thinkingThinking & Problem Solving | P3WorkingDe apoyo | Applies Critical thinking independently in normal and moderately complex situations. |
| Cross-functional collaborationCollaboration & Relationships | P3WorkingDe apoyo | Applies Cross-functional collaboration independently in normal and moderately complex situations. |
| Learning agilityExecution & Self-Management | P3WorkingDe apoyo | Applies Learning agility independently in normal and moderately complex situations. |
| Stakeholder alignmentInfluence & Leadership Without Authority | P3WorkingDe apoyo | Applies Stakeholder alignment independently in normal and moderately complex situations. |
| Structured problem solvingThinking & Problem Solving | P3WorkingDe apoyo | Applies Structured problem solving independently in normal and moderately complex situations. |
Profesionales7
| Profesionales | P | De apoyo |
|---|---|---|
| Analytics problem framingData & Analytics Practice | P3WorkingCentral | Applies Analytics problem framing independently in normal and moderately complex situations. |
| Data contracts governanceData & Analytics Practice | P3WorkingDe apoyo | Applies Data contracts governance independently in normal and moderately complex situations. |
| Data governanceCybersecurity, Privacy & Data Governance Standards | P3WorkingDe apoyo | Applies Data governance independently in normal and moderately complex situations. |
| Data product managementData & Analytics Practice | P3WorkingDe apoyo | Applies Data product management independently in normal and moderately complex situations. |
| Data quality managementCybersecurity, Privacy & Data Governance Standards | P3WorkingDe apoyo | Applies Data quality management independently in normal and moderately complex situations. |
| KPI designData & Analytics Practice | P3WorkingCentral | Applies KPI design independently in normal and moderately complex situations. |
| Metrics definitionData & Analytics Practice | P3WorkingCentral | Applies Metrics definition independently in normal and moderately complex situations. |
Técnicas12
| Técnicas | P | De apoyo |
|---|---|---|
| Apache SparkDatabases & Data Platforms | P3WorkingDe apoyo | Applies Apache Spark independently in normal production scenarios and troubleshoots common issues. |
| Dashboard developmentAnalytics, BI & Data Visualization | P3WorkingCentral | Applies Dashboard development independently in normal production scenarios and troubleshoots common issues. |
| Data catalog platformsDatabases & Data Platforms | P3WorkingDe apoyo | Applies Data catalog platforms independently in normal production scenarios and troubleshoots common issues. |
| Data contract implementationDatabases & Data Platforms | P3WorkingDe apoyo | Applies Data contract implementation independently in normal production scenarios and troubleshoots common issues. |
| Data lineage toolingDatabases & Data Platforms | P3WorkingDe apoyo | Applies Data lineage tooling independently in normal production scenarios and troubleshoots common issues. |
| Data modelingDatabases & Data Platforms | P3WorkingCentral | Applies Data modeling independently in normal production scenarios and troubleshoots common issues. |
| Data visualization implementationAnalytics, BI & Data Visualization | P3WorkingDe apoyo | Applies Data visualization implementation independently in normal production scenarios and troubleshoots common issues. |
| DatabricksDatabases & Data Platforms | P3WorkingDe apoyo | Applies Databricks independently in normal production scenarios and troubleshoots common issues. |
| Dimensional modelingDatabases & Data Platforms | P3WorkingCentral | Applies Dimensional modeling independently in normal production scenarios and troubleshoots common issues. |
| SQL analyticsAnalytics, BI & Data Visualization | P3WorkingCentral | Applies SQL analytics independently in normal production scenarios and troubleshoots common issues. |
| Semantic layer engineeringAnalytics, BI & Data Visualization | P3WorkingCentral | Applies Semantic layer engineering independently in normal production scenarios and troubleshoots common issues. |
| dbtDatabases & Data Platforms | P3WorkingCentral | Applies dbt independently in normal production scenarios and troubleshoots common issues. |
Qué cambia al pasar de L3 a L4
Moving from Senior Analytics Engineer to Staff 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 L4-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.