Analytics Engineering
Analytics Engineering is an individual-contributor Data + AI career progressing from guided delivery to enterprise expertise without requiring people management.
- Function
- Data & Analytics
- Archetype
- Engineering
- Highest level
- L6 · Principal Analytics Engineer
Why it exists
Transforms modeled data into governed analytical datasets, semantic models and trusted metrics for self-service analytics.
Typical responsibilities
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.
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 Analytics Engineer → Analytics Engineer → Senior Analytics Engineer → Staff Analytics Engineer → Senior Staff Analytics Engineer → Principal Analytics Engineer
Levels in this career
Six standard stages. The seventh exists only where the career provides for it.
What is expected at L1 · Associate Analytics Engineer
Apply analytics engineering 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 analytics engineering outcomes, makes sound trade-offs, communicates evidence and risks, and demonstrates the autonomy and impact expected at L1.
Typical evidence
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.
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 |
|---|---|---|
| Analytics problem framingData & Analytics Practice | P1AwarenessCore | Understands the purpose, vocabulary and basic principles of Analytics problem framing; works with close guidance. |
| Data governanceCybersecurity, Privacy & Data Governance Standards | P1AwarenessSupporting | 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 | P1AwarenessSupporting | Understands the purpose, vocabulary and basic principles of Data quality management; works with close guidance. |
| KPI designData & Analytics Practice | P1AwarenessCore | Understands the purpose, vocabulary and basic principles of KPI design; works with close guidance. |
| Metrics definitionData & Analytics Practice | P1AwarenessCore | Understands the purpose, vocabulary and basic principles of Metrics definition; works with close guidance. |
Technical8
| Technical | P | Supporting |
|---|---|---|
| Dashboard developmentAnalytics, BI & Data Visualization | P1AwarenessSupporting | Recognizes the purpose, core concepts and risks of Dashboard development; 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 modelingDatabases & Data Platforms | P1AwarenessCore | Recognizes the purpose, core concepts and risks of Data modeling; performs only guided exercises. |
| Data visualization implementationAnalytics, BI & Data Visualization | P1AwarenessSupporting | Recognizes the purpose, core concepts and risks of Data visualization implementation; performs only guided exercises. |
| Dimensional modelingDatabases & Data Platforms | P1AwarenessCore | Recognizes the purpose, core concepts and risks of Dimensional modeling; performs only guided exercises. |
| SQL analyticsAnalytics, BI & Data Visualization | P1AwarenessCore | Recognizes the purpose, core concepts and risks of SQL analytics; 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. |
| dbtDatabases & Data Platforms | P1AwarenessCore | Recognizes the purpose, core concepts and risks of dbt; performs only guided exercises. |
What changes from L1 to L2
Moving from Associate Analytics Engineer to Analytics Engineer 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.
- Data ArchitectureData & Analytics21 shared skills
- AI Governance & Responsible AIData & Analytics12 shared skills
- AI Platform & MLOps EngineeringData & Analytics12 shared skills
- Data AnalyticsData & Analytics15 shared skills
- Business IntelligenceData & Analytics15 shared skills
- Data EngineeringData & Analytics15 shared skills
Career framework v21, active since August 17, 2026.