Data Analytics
Data Analytics is an individual-contributor career path within Data & Analytics. Professionals progress from guided execution to independent delivery, senior problem solving, cross-team leadership and enterprise-level expertise without requiring people management.
- Function
- Data & Analytics
- Archetype
- Analyst
- Highest level
- L6 · Senior Principal Analyst
Why it exists
Enables the organization to deliver reliable outcomes in data analytics by building progressively deeper expertise, judgment, ownership and business impact.
Typical responsibilities
Execute discipline-specific work; apply professional standards; solve increasingly complex problems; collaborate with stakeholders; improve quality and efficiency; share expertise; at senior levels, shape practices and decisions beyond the immediate team.
Where the work happens
Common in Data & Analytics teams across technology companies, shared-services organizations, consulting firms, multinational operations and other employers that require data analytics capability.
How the career progresses
Associate Analyst → Analyst → Senior Analyst → Lead Analyst → Principal Analyst → Senior Principal Analyst
Levels in this career
Six standard stages. The seventh exists only where the career provides for it.
What is expected at L2 · Analyst
Independently delivers standard work within a team or defined domain. The focus is successful individual contribution at this stage, not people management.
The five dimensions that change
- Autonomy
- Works independently on routine work; seeks help for exceptions.
- Scope
- Owns complete assignments or a defined area.
- Complexity
- Standard problems with some judgment required.
- Influence
- Team and routine cross-functional partners.
- Business impact
- Predictable delivery, quality and customer/team outcomes.
- Ambiguity
- Low to moderate.
What good looks like
Analyst consistently demonstrates the expected autonomy and judgment for L2, delivers outcomes appropriate to the scope of the role, applies required Human, Professional and Technical skills at the mapped proficiency, and produces evidence of impact rather than relying on tenure alone.
Typical evidence
Completed work with measurable quality/outcome; stakeholder feedback; examples of problems solved and decisions made; reusable artifacts or improvements; demonstrated skill proficiency; mentoring/influence evidence at senior levels.
Skills expected at L2
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.
Human11
| Human | P | Supporting |
|---|---|---|
| AccountabilityExecution & Self-Management | P3WorkingCore | Applies the skill independently in normal and moderately complex situations. |
| Active listeningCommunication & Language | P3WorkingCore | Applies the skill independently in normal and moderately complex situations. |
| AdaptabilityExecution & Self-Management | P3WorkingCore | Applies the skill independently in normal and moderately complex situations. |
| Clear verbal communicationCommunication & Language | P3WorkingCore | Applies the skill independently in normal and moderately complex situations. |
| Clear written communicationCommunication & Language | P3WorkingCore | Applies the skill independently in normal and moderately complex situations. |
| CollaborationCollaboration & Relationships | P3WorkingCore | Applies the skill independently in normal and moderately complex situations. |
| Continuous learningExecution & Self-Management | P3WorkingCore | Applies the skill independently in normal and moderately complex situations. |
| Critical thinkingThinking & Problem Solving | P3WorkingCore | Applies the skill independently in normal and moderately complex situations. |
| ProfessionalismEthics & Professional Conduct | P3WorkingCore | Applies the skill independently in normal and moderately complex situations. |
| Structured problem solvingThinking & Problem Solving | P3WorkingCore | Applies the skill independently in normal and moderately complex situations. |
| Time managementExecution & Self-Management | P3WorkingCore | Applies the skill independently in normal and moderately complex situations. |
Professional6
| Professional | P | Supporting |
|---|---|---|
| Data product managementData & Analytics Practice | P2FoundationalCore | Applies the skill to routine work with guidance and follows established practices. |
| Data quality managementCybersecurity, Privacy & Data Governance Standards | P2FoundationalSupporting | Applies the skill to routine work with guidance and follows established practices. |
| Data stewardshipCybersecurity, Privacy & Data Governance Standards | P2FoundationalSupporting | Applies the skill to routine work with guidance and follows established practices. |
| Data storytellingData & Analytics Practice | P2FoundationalCore | Applies the skill to routine work with guidance and follows established practices. |
| User story definitionAgile, Product & Delivery Methods | P2FoundationalSupporting | Applies the skill to routine work with guidance and follows established practices. |
| Value stream managementAgile, Product & Delivery Methods | P2FoundationalSupporting | Applies the skill to routine work with guidance and follows established practices. |
Technical6
| Technical | P | Supporting |
|---|---|---|
| Azure Virtual MachinesCloud Platforms | P2FoundationalSupporting | Applies the skill to routine work with guidance and follows established practices. |
| Data pipeline orchestrationDatabases & Data Platforms | P2FoundationalCore | Applies the skill to routine work with guidance and follows established practices. |
| Data visualization implementationAnalytics, BI & Data Visualization | P2FoundationalCore | Applies the skill to routine work with guidance and follows established practices. |
| Data warehouse engineeringDatabases & Data Platforms | P2FoundationalCore | Applies the skill to routine work with guidance and follows established practices. |
| Microsoft AzureCloud Platforms | P2FoundationalSupporting | Applies the skill to routine work with guidance and follows established practices. |
| Python data analysisAnalytics, BI & Data Visualization | P2FoundationalCore | Applies the skill to routine work with guidance and follows established practices. |
What changes from L2 to L3
Moving from Analyst to Senior Analyst means demonstrating sustained performance at a larger scope with greater autonomy, complexity, influence and business impact—not simply spending more time in role.
How readiness is shown
Repeatedly performs key aspects of Senior Analyst before promotion; demonstrates the required skill increases; handles complex problems requiring analysis and trade-offs.; receives credible stakeholder evidence; shows measurable outcomes at the next-level scope.
How to prepare
Take stretch assignments at the next-level scope; deepen the listed skill gaps; seek feedback from experienced practitioners; document measurable outcomes and decisions; mentor/share knowledge where appropriate; pursue relevant learning or certification when it strengthens capability.
Adjacent careers
Computed from shared skills. It is a signal for exploring, not a hiring or eligibility guarantee.
- Business IntelligenceData & Analytics54 shared skills
- Data EngineeringData & Analytics52 shared skills
- Data ScienceData & Analytics50 shared skills
- AI / Generative AI EngineeringData & Analytics49 shared skills
- Machine Learning EngineeringData & Analytics46 shared skills
- Data Governance & StewardshipData & Analytics44 shared skills
Career framework v21, active since August 17, 2026.