Your data platform is at stage 2. You’re copying stage 5 patterns. That’s why it’s breaking.
Five stages I see across the SMEs and scaleups I work with:
Stage 1 - Scripts and spreadsheets. Founders extract CSVs and stitch them in Excel. Works fine until headcount hits ~30.
Stage 2 - First warehouse. Snowflake or BigQuery, dbt models, one analyst. Decisions get faster. Governance is still informal.
Stage 3 - Self-serve BI. Looker or Metabase, dashboards everywhere, conflicting metrics start appearing. The first “what does revenue mean?” Slack thread surfaces.
Stage 4 - Data products. Domain teams own datasets with SLAs. The platform team builds tooling, not pipelines. Ownership is explicit.
Stage 5 - Mesh or true platform. Federated governance, self-serve infrastructure, domain-owned everything. This is Spotify and Zalando, not your 80-person scaleup.
The trap is mostly stage 2 teams reading Netflix engineering blogs and adopting stage 5 patterns. Six months later they have a data mesh nobody asked for and dashboards still take three weeks.
What breaks at each transition:
- Stage 2 to 3: governance and metric definitions
- Stage 3 to 4: ownership and accountability
- Stage 4 to 5: org design (Conway’s Law catches up)
Diagnose your actual stage and address that stage’s specific failure mode. Tools alone won’t move you up.
What stage is your data platform at - honestly?