data classification jobs in 2026 — demand, top roles hiring, and related skills
As of 2026-10-29, data classification appears in 455 job postings indexed by Skillenai over the past 90 days — Security Engineer has the most postings mentioning data classification, with demand share up 4.9% vs the prior 4 weeks.
Last updated · 90d ending 2026-10-29
Which roles want data classification?
Upload your resume and Skillenai will show which roles your data classification experience fits, which skills you already cover, and what is missing.
Frequently asked questions about data classification
+Is data classification in demand in 2026?
Yes. data classification appears in 455 job postings indexed by Skillenai over the 90 days ending 2026-10-29. Security Engineer accounts for the most postings mentioning data classification (6.4% of all postings mentioning data classification).
+What jobs require data classification?
According to the Skillenai jobs index over the 90 days ending 2026-10-29, among roles with at least 20 postings, the highest shares mentioning data classification are Data Security Engineer (53.6% of that role’s postings mention data classification), Data Governance Manager (18.5% of that role’s postings mention data classification), Security Solution Architect (14.8% of that role’s postings mention data classification).
+What skills are commonly paired with data classification?
Across job postings indexed by Skillenai (90 days ending 2026-10-29), data classification most often appears alongside data governance, Python, data lineage, SQL, data quality.
+Where is data classification most in demand?
As of 2026-10-29, the metro areas posting the most jobs requiring data classification are New York City, San Francisco, London, Amsterdam, Bengaluru, according to the Skillenai jobs index.
+How can I keep up with new data classification content and jobs?
Skillenai indexes news, blog posts, and research papers mentioning data classification alongside the jobs index. You can subscribe to a daily email digest of new data classification content from your Skillenai account.
+Which skills come before and after data classification?
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 data classification — last 90 days
Salary distribution
Box = 25th–75th percentile · tick = median · whisker = 10th–90th · USD, annualized
Career paths around data classification
Skills documented before and after this skill across employer changes.
Historical career profiles · all locations
Skills before data classification
Skills after data classification
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: HIPAA | 3 |
| Before: AWS | 2 |
| Before: data protection | 1 |
| Before: web development | 1 |
| Before: test cases | 1 |
| Before: C# | 1 |
| Before: multi-factor authentication | 1 |
| Before: DLP | 1 |
| After: optimization | 1 |
| After: automation | 1 |
| After: Continuous Delivery | 1 |
| After: data accuracy | 1 |
| After: Query logs | 1 |
| After: IAM | 1 |
| After: competitive benchmarking | 1 |
| After: regular expressions | 1 |
Roles most likely to require data classification
Among roles with at least 20 postings in the same period.
| Role | Postings mentioning skill | % of role postings mentioning skill |
|---|---|---|
| Data Security Engineer | 15 | 53.6% |
| Data Governance Manager | 5 | 18.5% |
| Security Solution Architect | 4 | 14.8% |
| Sales Systems Engineer | 3 | 12.0% |
| Data Solutions Architect | 2 | 9.1% |
| AI Governance Lead | 2 | 8.3% |
| IT Security Analyst | 4 | 7.8% |
| Business Information Security Officer | 2 | 7.1% |
| IT Security Engineer | 4 | 7.0% |
| Security Consultant | 4 | 6.7% |
Roles with the most data classification postings
| Role | Postings mentioning skill | Share of skill postings |
|---|---|---|
| Security Engineer | 29 | 6.4% |
| Product Manager | 19 | 4.2% |
| Data Engineer | 18 | 4.0% |
| Software Engineer | 16 | 3.5% |
| Data Architect | 15 | 3.3% |
| Data Security Engineer | 15 | 3.3% |
| Data Analyst | 10 | 2.2% |
| Information Security Engineer | 10 | 2.2% |
| Data Governance Lead | 7 | 1.5% |
| Business Systems Security Analyst | 6 | 1.3% |
Top companies posting jobs requiring data classification
Employers ranked by indexed job postings in the last 90 days.
| Company | Postings · 90 days |
|---|---|
| Wrike | 8 |
| Mastercard | 7 |
| Pure Storage | 7 |
| State Street | 7 |
| SVB | 6 |
| Booking.com | 6 |
| Accenture | 6 |
| Cohesity | 5 |
| Sopra Steria | 5 |
| Capco | 5 |
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 data classification
| Name | Postings | Share |
|---|---|---|
| New York City | 13 | 2.9% |
| San Francisco | 11 | 2.4% |
| London | 8 | 1.8% |
| Amsterdam | 7 | 1.5% |
| Bengaluru | 6 | 1.3% |
| Bogotá | 6 | 1.3% |
| Prague | 6 | 1.3% |
| Austin | 5 | 1.1% |
| Seattle | 5 | 1.1% |
Skills commonly paired with data classification
Explore related pages
How this was computed
Weekly job-count charts omit the incomplete current week (weeks start Monday, UTC). Totals include all postings in the stated window. Counts derive from the Skillenai jobs index over the 90 days ending 2026-10-29. 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 data classification by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s data classification postings by all data classification 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). Adjusted posting share: 0.2% to 0.2%. Demand share change is the relative percentage change between these adjusted shares. Each employer-and-ATS group has at least 10 postings in each 90-day window; its earlier posting count supplies the same weight in both windows. The panel includes 2,482 identified employers and covers 71% of earlier and 70% of latest indexed postings. Windows: 2026-06-30 to 2026-09-28 and 2026-07-28 to 2026-10-26 (UTC; end dates excluded). The windows overlap by 62 days. Dates reflect indexing, not the employer’s posting date. This measures posting mix, not total hiring or market-wide demand. Matching excludes entrants and exits; changes in crawl completeness within an employer or ATS can still affect the result.
- source
- Skillenai jobs index, deduplicated daily
- entity_id
- 0abfd9b780626a94
- data_as_of
- 2026-10-29
- window_days
- 90