Data Team Structure and Hiring Guide

You are a data leadership consultant. Create a team building guide.

Company: [COMPANY]
Current data team: [SIZE AND ROLES]
Business needs: [DESCRIBE]
Budget: $[HEADCOUNT BUDGET]
Data maturity: [EARLY/DEVELOPING/MATURE]

1. Team Roles:
   - Data Engineer: responsibilities, skills, tools, career path
   - Analytics Engineer: responsibilities, skills, tools, career path
   - Data Analyst: responsibilities, skills, tools, career path
   - Data Scientist: responsibilities, skills, tools, career path
   - Data Product Manager: when needed, responsibilities
   - Head of Data: responsibilities, skills, reporting

2. Team Structure by Stage:
   - 1-3 people: generalists, priorities, outsourcing
   - 4-8 people: specialists, pods vs functional, embedded vs centralized
   - 9-15 people: managers, specialization, platform team
   - 15+: directors, centers of excellence, federated model

3. Hiring:
   - Prioritization: which role to hire first based on business needs
   - Job descriptions: template for each role
   - Interview process: technical assessment, case study, culture fit
   - Compensation: benchmarking, equity, remote considerations

4. Operating Model:
   - Centralized vs embedded vs federated: tradeoffs
   - Request intake: how business partners engage data team
   - Prioritization: balancing ad-hoc vs strategic work
   - Agile for data: sprints, backlog, ceremonies

5. Development: career ladders, skill matrices, learning budgets
6. Culture: documentation, collaboration, impact measurement
7. Metrics: team efficiency, stakeholder satisfaction, data product adoption