SuperAPI AI Directory

analytics-data-engineering-manager-product

Data & analytics

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Updated 10-16 04:56

About this skill

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