| name | analytics-data-engineering-manager-product |
| description | Guides managers of product-embedded analytics engineering teams—org design, hiring and levels,
roadmap and prioritization with product managers, analytics data product delivery, squad
alignment, stakeholder forums, team KPIs, and escalation paths for metric and mart quality.
Use when leading analytics engineers on product domains, planning analytics roadmaps per product
area, resolving prioritization across squads, or defining how marts and metrics ship with
features—not for hands-on dbt/SQL (analytics-data-engineer), enterprise data platform ADRs
(data-architect), company-wide data governance ops (data-manager), or dashboard UX (bi-analyst).
For vertical copilot/RAG product engineering management, use
engineering-manager-vertical-ai-products—not analytics-data-engineering-manager-product.
|
Analytics Data Engineering Manager, Product
When to Use
- Design or scale a product-embedded analytics engineering org
- Prioritize analytics backlog with product managers and domain leads
- Define analytics data products (marts, metrics packs) tied to product launches
- Run delivery cadence: intake, estimation, dependencies with app/data platform teams
- Set team KPIs (freshness, test pass rate, time-to-metric for launches)
- Hire, level, and develop analytics engineers and leads
- Escalate cross-squad conflicts (metric definitions, shared dimensions, capacity)
When NOT to Use
- Writing or refactoring dbt models →
analytics-data-engineer
- Warehouse partition tuning or ETL platform design →
data-warehouse-engineer
- Enterprise mesh, governance program, catalog policy →
data-architect or data-manager
- Dashboard design and executive storytelling →
bi-analyst
- Multi-portfolio technical programs (non-analytics) →
technical-program-manager
- BRD/process mapping without analytics delivery →
business-analyst
Related skills
| Need | Skill |
|---|
| dbt implementation detail | analytics-data-engineer |
| Org-wide data ops and governance cadence | data-manager |
| BI and KPI storytelling | bi-analyst |
| Business rules sign-off | business-analyst |
| Platform architecture | data-architect |
| Large cross-functional program | technical-program-manager |
Core Workflows
1. Org design and squad model
Embedded vs centralized analytics engineering; ratios; interfaces to DE and BI.
See references/team_org_design.md.
2. Roadmap and prioritization
Product-domain backlog, launch-aligned milestones, capacity trade-offs.
See references/roadmap_prioritization.md.
3. Delivery and launch alignment
Definition of done for analytics with feature releases; dependency management.
See references/delivery_launch_alignment.md.
4. Stakeholder partnerships
PM, product analytics, finance, legal/privacy, platform engineering forums.
See references/stakeholder_partnerships.md.
5. Hiring and career development
Levels, interview loops, growth plans, performance calibration inputs.
See references/hiring_development.md.
6. Metrics and accountability
Team scorecard, product analytics SLAs, incident and quality escalation.
See references/team_metrics_accountability.md.
Output standards
- Roadmap items link business outcome, metric/mart deliverable, and owner
- Launch checklist signed by PM + analytics eng before GA
- Escalations documented with options and recommendation
- No redefining enterprise architecture without
data-architect ADR
When to load references
- Org →
references/team_org_design.md
- Roadmap →
references/roadmap_prioritization.md
- Delivery →
references/delivery_launch_alignment.md
- Stakeholders →
references/stakeholder_partnerships.md
- People →
references/hiring_development.md
- KPIs →
references/team_metrics_accountability.md
