Data Analytics PM Guide
Data PMs build the tools other PMs, analysts, and data scientists rely on. Technical depth is table stakes — SQL, warehouses, and BI semantics.
$275B+ market
Market Size
25-28% annually
Growth Rate
$155K-$200K
Salary Range
Key PM Challenges
- Users are technical — no room for hand-waving
- Query performance is UX
- Semantics: what a metric means matters more than the number
- Warehouse costs balloon with usage
- Governance vs self-serve tension
Critical Metrics to Track
- Weekly active queries
- Query success rate
- Query latency (p50/p95)
- Warehouse spend per user
- Dashboards created per user
- Time-to-first-insight
- Model reuse rate
- Data-quality incident count
Leading Companies
Databricksdbt LabsLooker (Google Cloud)MixpanelSnowflakeTableauPowerBIThoughtSpotAmplitudeSegment
Common Tools & Platforms
SQLdbtSnowflake / BigQuery / RedshiftLooker / Tableau / MetabaseAmplitudeAirflowFivetranGreat Expectations
PM Specializations in Data & Analytics
Warehouse PM
Ingest, compute, storage, and cost controls
BI PM
Dashboards, exploration, and semantic layers
ML Platform PM
Feature stores, model registry, and serving
Data Quality PM
Tests, lineage, freshness, and alerting
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