time-series data jobs in 2026 — demand, top roles hiring, and related skills
As of 2026-09-30, time-series data appears in 106 job postings indexed by Skillenai over the past 90 days — Software Engineer has the most postings mentioning time-series data.
Last updated · 90d ending 2026-09-30
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Frequently asked questions about time-series data
+Is time-series data in demand in 2026?
Yes. time-series data appears in 106 job postings indexed by Skillenai over the 90 days ending 2026-09-30. Software Engineer accounts for the most postings mentioning time-series data (17.9% of all postings mentioning time-series data).
+What jobs require time-series data?
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 time-series data are Applied Machine Learning Engineer (4.2% of that role’s postings mention time-series data), Detection Engineer (3.6% of that role’s postings mention time-series data), Applied AI Scientist (3.4% of that role’s postings mention time-series data).
+What skills are commonly paired with time-series data?
Across job postings indexed by Skillenai (90 days ending 2026-09-30), time-series data most often appears alongside Python, machine learning, observability, data pipelines, Java.
+Where is time-series data most in demand?
As of 2026-09-30, the metro areas posting the most jobs requiring time-series data are London, San Carlos, New York City, San Francisco, Boston, according to the Skillenai jobs index.
+How can I keep up with new time-series data content and jobs?
Skillenai indexes news, blog posts, and research papers mentioning time-series data alongside the jobs index. You can subscribe to a daily email digest of new time-series data content from your Skillenai account.
+Which skills come before and after time-series data?
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 time-series data — last 90 days
Career paths around time-series data
Skills documented before and after this skill across employer changes.
Historical career profiles · all locations
Skills before time-series data
Skills after time-series data
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: docker | 2 |
| Before: sql | 2 |
| Before: Azure | 2 |
| Before: Excel | 2 |
| Before: spark | 1 |
| Before: C# | 1 |
| Before: ETL | 1 |
| Before: a/b testing | 1 |
| After: python | 3 |
| After: Git | 2 |
| After: ci/cd | 2 |
| After: PySpark | 2 |
| After: ETL | 1 |
| After: SNS | 1 |
| After: Jupyter | 1 |
| After: DynamoDB | 1 |
Roles most likely to require time-series data
Among roles with at least 20 postings in the same period.
| Role | Postings mentioning skill | % of role postings mentioning skill |
|---|---|---|
| Applied Machine Learning Engineer | 1 | 4.2% |
| Detection Engineer | 1 | 3.6% |
| Applied AI Scientist | 1 | 3.4% |
| Observability Engineer | 1 | 3.4% |
| Deployment Strategist | 2 | 3.3% |
| Data Product Owner | 1 | 3.1% |
| Scientist | 1 | 2.5% |
| Cloud Data Engineer | 1 | 1.8% |
| Backend Software Engineer | 8 | 1.4% |
| AI Research Engineer | 1 | 1.0% |
Roles with the most time-series data postings
| Role | Postings mentioning skill | Share of skill postings |
|---|---|---|
| Software Engineer | 19 | 17.9% |
| Backend Software Engineer | 8 | 7.5% |
| Data Scientist | 8 | 7.5% |
| Engineering Manager | 8 | 7.5% |
| Data Engineer | 7 | 6.6% |
| Product Manager | 3 | 2.8% |
| QA Engineer | 3 | 2.8% |
| R&D Data Engineer | 3 | 2.8% |
| Applied Scientist | 2 | 1.9% |
| Deployment Strategist | 2 | 1.9% |
Top companies posting jobs requiring time-series data
Employers ranked by indexed job postings in the last 90 days.
| Company | Postings · 90 days |
|---|---|
| Elastic | 10 |
| BeaconOS | 8 |
| General Motors | 5 |
| Anthropic | 4 |
| Referralsuseonly | 4 |
| Celonis | 3 |
| Tulip Interfaces | 3 |
| Graphcore | 3 |
| Axle-careers | 3 |
| Lydian | 3 |
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 time-series data
| Name | Postings | Share |
|---|---|---|
| London | 8 | 7.5% |
| San Carlos | 8 | 7.5% |
| New York City | 7 | 6.6% |
| San Francisco | 5 | 4.7% |
| Boston | 3 | 2.8% |
| Gdańsk | 3 | 2.8% |
| Mountain View | 3 | 2.8% |
| Redwood City | 3 | 2.8% |
| Somerville | 3 | 2.8% |
Skills commonly paired with time-series data
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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 time-series data by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s time-series data postings by all time-series data 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
- 08534d453166b321
- 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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