Pivot tables jobs in 2026 — demand, top roles hiring, and related skills
As of 2026-09-30, Pivot tables appears in 490 job postings indexed by Skillenai over the past 90 days — Data Analyst has the most postings mentioning Pivot tables.
Last updated · 90d ending 2026-09-30
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Frequently asked questions about Pivot tables
+Is Pivot tables in demand in 2026?
Yes. Pivot tables appears in 490 job postings indexed by Skillenai over the 90 days ending 2026-09-30. Data Analyst accounts for the most postings mentioning Pivot tables (14.9% of all postings mentioning Pivot tables).
+What jobs require Pivot tables?
According to the Skillenai jobs index over the 90 days ending 2026-09-30, among roles with at least 20 postings, the highest shares mentioning Pivot tables are Operations Analyst (12.9% of that role’s postings mention Pivot tables), Data Business Analyst (12.5% of that role’s postings mention Pivot tables), Material Program Manager (11.1% of that role’s postings mention Pivot tables).
+What skills are commonly paired with Pivot tables?
Across job postings indexed by Skillenai (90 days ending 2026-09-30), Pivot tables most often appears alongside SQL, Excel, Power BI, Tableau, Microsoft Excel.
+Where is Pivot tables most in demand?
As of 2026-09-30, the metro areas posting the most jobs requiring Pivot tables are New York City, Toronto, Chicago, Hyderabad, Pune, according to the Skillenai jobs index.
+How can I keep up with new Pivot tables content and jobs?
Skillenai indexes news, blog posts, and research papers mentioning Pivot tables alongside the jobs index. You can subscribe to a daily email digest of new Pivot tables content from your Skillenai account.
+Which skills come before and after Pivot tables?
The skill-flow chart shows skills documented in adjacent positions across observed employer changes. An outgoing skill is documented in the following position but not the preceding one. These are ideas to explore, not proven prerequisites, acquisition dates, or levels of mastery. Each ribbon counts employer moves with that skill pair; one move can contribute several pairs.
Weekly indexed postings requiring Pivot tables — last 90 days
Salary distribution
Box = 25th–75th percentile · tick = median · whisker = 10th–90th · USD, annualized
Career paths around Pivot tables
Skills documented before and after this skill across employer changes.
Historical career profiles · all locations
Skills before Pivot tables
Skills after Pivot tables
How to read this chart · view counts
Each side is an independent set of observed employer moves, not the same people followed through three stages. Ribbon widths compare move counts within that side. Internal moves are not included.
The following position documents a skill that the preceding position does not. Skills must be linked to both positions, with clear dates and no overlap. One move can connect several skill pairs. These patterns suggest skills to explore; they do not establish prerequisites, when a skill was learned, or a higher skill level.
Source: Skillenai talent graph, historical career profiles. Historical descriptions and coverage can change. Only the leading published connections are shown.
| Connection | Moves |
|---|---|
| Before: Excel | 32 |
| Before: sql | 25 |
| Before: python | 16 |
| Before: Tableau | 15 |
| Before: Power BI | 14 |
| Before: Powerpoint | 6 |
| Before: SAP | 6 |
| Before: Microsoft Excel | 6 |
| After: python | 30 |
| After: sql | 24 |
| After: Tableau | 21 |
| After: Power BI | 20 |
| After: pandas | 10 |
| After: a/b testing | 9 |
| After: ETL | 8 |
| After: SAS | 8 |
Roles most likely to require Pivot tables
Among roles with at least 20 postings in the same period.
| Role | Postings mentioning skill | % of role postings mentioning skill |
|---|---|---|
| Operations Analyst | 9 | 12.9% |
| Data Business Analyst | 3 | 12.5% |
| Material Program Manager | 8 | 11.1% |
| People Analytics Analyst | 3 | 11.1% |
| Business Operations Analyst | 3 | 9.4% |
| Sales Operations Analyst | 5 | 8.2% |
| Analytics Analyst | 4 | 8.0% |
| Pricing Analyst | 3 | 7.9% |
| Financial Data Analyst | 2 | 5.3% |
| Business Analyst Intern | 1 | 5.0% |
Roles with the most Pivot tables postings
| Role | Postings mentioning skill | Share of skill postings |
|---|---|---|
| Data Analyst | 73 | 14.9% |
| Business Analyst | 41 | 8.4% |
| Program Manager | 23 | 4.7% |
| Operations Analyst | 9 | 1.8% |
| Product Manager | 9 | 1.8% |
| Business Intelligence Analyst | 8 | 1.6% |
| Material Program Manager | 8 | 1.6% |
| Analyst | 5 | 1.0% |
| Business Data Analyst | 5 | 1.0% |
| Control Account Manager (CAM) | 5 | 1.0% |
Top companies posting jobs requiring Pivot tables
Employers ranked by indexed job postings in the last 90 days.
| Company | Postings · 90 days |
|---|---|
| Amazon | 19 |
| Telus | 10 |
| Globalpr | 8 |
| Uber Freight | 8 |
| Clara | 6 |
| WPP | 5 |
| VaynerMedia | 5 |
| Maersk | 4 |
| Voyager Technologies | 4 |
| RTX | 4 |
Job postings indexed over the past 90 days, grouped by resolved employer. Counts are postings, not hires. Companies without a published page appear without a link.
Top metros hiring for Pivot tables
| Name | Postings | Share |
|---|---|---|
| New York City | 22 | 4.5% |
| Toronto | 9 | 1.8% |
| Chicago | 5 | 1.0% |
| Hyderabad | 5 | 1.0% |
| Pune | 5 | 1.0% |
| Barcelona | 4 | 0.8% |
| Boston | 4 | 0.8% |
| Bucharest | 4 | 0.8% |
| Gurugram | 4 | 0.8% |
Skills commonly paired with Pivot tables
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How this was computed
Counts derive from the Skillenai jobs index over the 90 days ending 2026-09-30. Skills are resolved against the Skillenai canonical taxonomy, so the same entity is counted whether a posting writes 'Python', 'Python 3', or 'python'. Role prevalence divides postings mentioning Pivot tables by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s Pivot tables postings by all Pivot tables postings, including postings without a role. Shares need not sum to 100% for the displayed roles. Pages refresh weekly (or daily for the top-50 most-requested skills). An adjusted trend is not shown because comparable posting coverage is insufficient.
- source
- Skillenai jobs index, deduplicated daily
- entity_id
- a282f4a146cfad6a
- data_as_of
- 2026-09-30
- window_days
- 90
The demand, skills, and geo numbers on this page come from the same Skillenai labor market index that powers our API. Use it for compensation benchmarking, hiring-competition analysis, and skill-adoption tracking.
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