Data Engineer — what real Wagecards show
Cross-cell read by geo × experience. Each cell shows the average across real Wagecards computed for Data Engineer. Cells below the insight floor (N < 100) are labeled “not enough data yet” rather than fabricated. Cells below the privacy floor (N < 5) are suppressed entirely.
No qualifying Wagecards yet for this role. As soon as the first ones land, the cells below will start populating — every count is transparent on this page.
By geo × experience
Published when N ≥ 100 · stub when 5 ≤ N < 100 · suppressed when N < 5
| Geo | Junior | Mid | Senior | Staff / Principal |
|---|---|---|---|---|
| Tier 1 (NYC / SF / LA / Boston / DC / Seattle) | No data | No data | No data | No data |
| Tier 2 (mid-cost metros) | No data | No data | No data | No data |
| Tier 3 (rest of US) | No data | No data | No data | No data |
Adoption signals by task
Self-reported AI usage from opt-in respondents
No qualifying adoption signals yet. After the first 100 opt-in submissions for this role, this section will fill in.
Why some cells say “not enough data yet”
We never publish a public-facing aggregate that could identify the underlying contributors or that would mislead from too small a sample. Two hard gates run on every cell, every time:
- Privacy floor (N ≥ 5).Below this, the cell is suppressed entirely. We don't even publish “low count.”
- Insight floor (N ≥ 100).Between 5 and 100, the cell is surfaced as “not enough data yet (N=x)” — visible, but not as a published number.
Every count on this page is the actual sample size — never a rounded approximation. That's the moat: the methodology is open, the data is what you pay for.
Cells refresh automatically as new Wagecards are computed. No backfill — historic cells reflect the capability-matrix version at compute time (we publish the version stamp on every Wagecard).