Data Analyst & Steward

01Scope and Impact

You are an autonomous contributor holding end-to-end stewardship accountability for an assigned scope, on behalf of the business owners of that data. You balance stewardship responsibilities, analytics delivery, and self-service enablement while maximizing business value from data through trusted metrics, high-quality data products, and adoption of analytical solutions.

You may sit within a regional IT organization or directly within the business domain, depending on structure.

As a domain resource, you receive governance standards, tooling, and escalation support from the central Data & AI Governance function, Global Data & AI Platform team and the visualization engineering CoE.

02What you do

Metrics & Data Products

• Align existing and new metric definitions across teams so everyone works from the same numbers. 
• Curate metric definitions, metadata, and the semantic layer so they're reliable enough for AI agents to answer business questions directly, not just for human dashboard users. 
• Act as Data Steward for all data products within your assigned sub-domain. 
• Monitor and improve data quality through controls and remediation activities, elevating data quality and data management from source to the analytical layer. 
• Maintain metadata, data lineage, business glossaries, and ownership information within the enterprise data catalog. 
• Track and demonstrate the business value and ROI realized from the data products you steward, using this evidence to prioritize improvements or retirement.
• Partner with Data Engineers to define the semantic layer in the global data and AI platform and understand how they built data models and pipelines. 
• Review and coordinate data access approvals and stewardship workflows in accordance with governance policies and business ownership responsibilities. 

Analytical Solutions

• Support business stakeholders with complex, non-standard analytical questions that go beyond self-service, applying analytical rigor to validate findings before they inform decisions. 
• Drive adoption of self-service analytics developed with data engineers. 
• Build and maintain complex dashboards and analytical solutions. 
• Validate that self-service and analytical outputs remain accurate when consumed by AI agents, not only by human users. 

Data Literacy 

• Take ownership for growing data literacy within your sub-domain. 
• Train and support business users on self-service analytics solutions 

AI-readiness & Ways of Working 

• Proactively automates routine parts of their own workflow (quality checks, documentation updates, recurring reporting) using agentic AI, and prototypes solutions live with business stakeholders using AI instead of running a traditional multi-week build cycle. 

Öppen för alla Vi fokuserar på din kompetens, inte dina övriga förutsättningar. Vi är öppna för att anpassa rollen eller arbetsplatsen efter dina behov.