Data Engineering

Analytics Engineering

Analytics Engineers build the bridge between raw data and business decisions, mastering both technical depth and stakeholder translation. This path creates CDOs who speak fluent boardroom while architecting enterprise-scale data strategies.

L1 – L9 · 9 tours Leads to: CDO → What's a Reference DRS?

The Career Arc

Rotational · L1–L3

Build the Analytics Engineering craft. Prove you can wield the tools of Data Engineering.

  • L1 : Learn analytics engineering through model development
  • L2 : Build and maintain transformation models
  • L3 : Own data domains with strong modeling skills

Transformational · L4–L7

Deliver Analytics Engineering outcomes — each Data Engineering tour at this altitude has a defined mission and success criteria.

  • L4 : Lead analytics engineering projects
  • L5 : Drive analytics architecture across the org
  • L6 : Set analytics engineering direction
  • L7 : Shape the company's analytics vision

Manage a Team?

Great Analytics Engineering managers are practitioners first. The Data Engineering IC responsibilities in L4–L7 are your foundation — your management responsibilities are additive:

  • Hire people you'd trust locked in a room—skills matter, but trust matters more
  • Build a team that balances technical depth with business curiosity
  • Run 1:1s that connect data work to business impact—not just sprint tickets
  • Give feedback that builds both technical and communication skills
  • Remove blockers—fight for data access, compute resources, and stakeholder clarity

Foundational · L8–L9

Shape the Data Engineering organization from the Analytics Engineering chair — build institutions, not just products.

  • L8 : Build and lead analytics engineering teams
  • L9 : Own analytics engineering strategy
→ C-Suite: L10 is the CDO path — a distinct page, not duplicated here.

L1 — Associate Analytics Engineer Rotational

Mission

Learn analytics engineering through model development

This tour of duty

Build your first production dbt models

Own the outcomes

  • Learn dbt and analytics engineering fundamentals
  • Write SQL transformations under engineer guidance
  • Build data tests and quality checks
  • Build foundational knowledge of dimensional modeling
  • Participate in code reviews and model discussions
  • Document data models and business logic

Analytics Engineering at L1 — the competency bar

Data Engineering
2
Software Engineering
2
Analytics & BI
1

AI in this role

  • Generating SQL transformations
  • Debugging model issues
  • Writing dbt tests

L2 — Junior Analytics Engineer Rotational

Mission

Build and maintain transformation models

This tour of duty

Own a data domain that analysts depend on

Own the outcomes

  • Build and maintain dbt models for data domains
  • Define business logic in the transformation layer
  • Implement data quality testing and documentation
  • Collaborate with analysts on modeling requirements
  • Troubleshoot data quality issues independently
  • Create model documentation and metadata

Analytics Engineering at L2 — the competency bar

Data Engineering
2
Analytics & BI
2
Product Management
1
Software Engineering
1
Operational Excellence
1

AI in this role

  • Drafting model architectures
  • Analyzing data quality
  • Generating documentation

L3 — Senior Analytics Engineer Rotational

Mission

Own data domains with strong modeling skills

This tour of duty

Lead a project that improves data quality or accessibility

Own the outcomes

  • Own transformation layer for major data domains
  • Design dimensional models and semantic layers
  • Build metric definitions and business logic
  • Partner with analysts on data modeling standards
  • Develop reusable macros and patterns
  • Mentor junior engineers on dbt practices

Analytics Engineering at L3 — the competency bar

Data Engineering
3
Analytics & BI
2
Product Management
1
Software Engineering
1
Operational Excellence
1

AI in this role

  • Modeling data schemas
  • Reviewing dbt code
  • Creating lineage docs

L4 — Staff Analytics Engineer / Manager, Analytics Engineering Transformational

Mission

Lead analytics engineering projects

This tour of duty

Design data models that become company standards

Own the outcomes

  • Lead analytics engineering projects
  • Design scalable data modeling architectures
  • Establish data modeling standards and practices
  • Mentor engineers on analytics engineering
  • Influence technology decisions for analytics stack
  • Build relationships with analytics teams

Analytics Engineering at L4 — the competency bar

Data Engineering
3
Analytics & BI
2
Software Engineering
2
Product Management
1
Operational Excellence
1

AI in this role

  • Designing data marts
  • Analyzing usage patterns
  • Generating specs

L5 — Senior Staff Analytics Engineer / Senior Manager, Analytics Engineering Transformational

Mission

Drive analytics architecture across the org

This tour of duty

Drive modeling decisions across teams

Own the outcomes

  • Define analytics engineering strategy
  • Set technical standards for data modeling
  • Lead complex data modeling initiatives
  • Drive modeling best practice adoption
  • Shape analytics engineering org-wide
  • Represent analytics engineering in planning

Analytics Engineering at L5 — the competency bar

Data Engineering
4
Analytics & BI
3
Software Engineering
2
Product Management
1
Operational Excellence
1

AI in this role

  • Evaluating modeling approaches
  • Building architecture docs
  • Creating roadmaps

L6 — Director, Analytics Engineering Transformational

Mission

Set analytics engineering direction

This tour of duty

Define analytics engineering standards

Own the outcomes

  • Define analytics layer vision and roadmap
  • Architect data modeling standards and semantic layers that scale
  • Solve the most complex analytics engineering and data quality challenges
  • Own data quality and self-serve metrics
  • Drive organizational alignment on modeling
  • Represent analytics engineering in executive discussions

Analytics Engineering at L6 — the competency bar

Data Engineering
4
Analytics & BI
3
Software Engineering
3
Strategy
2
Product Management
1
Operational Excellence
1

AI in this role

  • Analyzing modeling patterns
  • Generating standards
  • Building knowledge bases

L7 — Senior Director, Analytics Engineering Transformational

Mission

Shape the company's analytics vision

This tour of duty

Solve a modeling problem that unlocks insights

Own the outcomes

  • Set analytics engineering strategy company-wide
  • Align analytics engineering with business goals
  • Build hiring and development for team
  • Define industry-leading modeling capabilities
  • Shape company-wide analytics operating model
  • Lead analytics engineering planning

Analytics Engineering at L7 — the competency bar

Data Engineering
2
Analytics & BI
2
Strategy
2
Product Management
1
Software Engineering
1
Operational Excellence
1

AI in this role

  • Modeling data evolution
  • Analyzing trends
  • Creating vision documents

L8 — VP, Analytics Engineering Foundational

Mission

Build and lead analytics engineering teams

This tour of duty

Build a team that delivers trusted data

Own the outcomes

  • Own analytics engineering outcomes at scale
  • Drive transformation for analytics excellence
  • Build systems for data quality and accessibility
  • Shape company strategy through analytics lens
  • Establish operating model for analytics org
  • Lead cross-functional analytics alignment

Analytics Engineering at L8 — the competency bar

Data Engineering
2
Software Engineering
2
Analytics & BI
1
Strategy
1

AI in this role

  • Building analytics dashboards
  • Analyzing team patterns
  • Creating hiring frameworks

L9 — SVP of Analytics Engineering Foundational

Mission

Own analytics engineering strategy

This tour of duty

Transform analytics engineering practices

Own the outcomes

  • Shape company analytics engineering vision
  • Represent analytics engineering at executive level
  • Define multi-year analytics infrastructure roadmap
  • Build partnerships and industry relationships
  • Lead analytics engineering through transitions
  • Establish analytics engineering as differentiator

Analytics Engineering at L9 — the competency bar

Software Engineering
2
Data Engineering
1
Analytics & BI
1
Strategy
1

AI in this role

  • Modeling analytics scenarios
  • Building strategy documents
  • Designing knowledge infrastructure

What Hiring Managers Look For

You transform raw data into clean, tested models that analysts can trust — showing you understand both engineering rigor and business logic.

You've built data infrastructure that scales beyond your current team's needs while maintaining sub-second query performance on production dashboards.

You architect data strategies that directly influence C-suite decisions, with documented cases of your models preventing million-dollar mistakes.

Common Career Transitions

Analytics Engineering → Product Analytics at L4-L5 for direct business impact measurement

Analytics Engineering → Data Platform at L5-L6 for broader infrastructure ownership

Analytics Engineering → Business Intelligence at L6+ for strategic decision-making leadership

Official Classifications

System Code Official Title
O*NET-SOC (US) 15-1243.01 Data Warehousing Specialists
ISCO-08 (UN/ILO) 2521 Database designers and administrators
ESCO (EU) data warehouse designer
SSOC 2024 (Singapore) 25210 Database Designers and Administrators
NCO-2015 (India) 2521.0100 Database Designer and Administrator

At L6 and above, the manager classification 1330 — Information and communications technology service managers applies IN ADDITION to the professional code — a manager is a superset of the individual contributor, never a replacement.

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