data acquisition jobs in 2026 — demand, top roles hiring, and related skills
As of 2026-09-30, data acquisition appears in 523 job postings indexed by Skillenai over the past 90 days — Test Engineer has the most postings mentioning data acquisition, with demand share up 4.7% vs the prior 4 weeks.
Last updated · 90d ending 2026-09-30
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Frequently asked questions about data acquisition
+Is data acquisition in demand in 2026?
Yes. data acquisition appears in 523 job postings indexed by Skillenai over the 90 days ending 2026-09-30. Test Engineer accounts for the most postings mentioning data acquisition (10.9% of all postings mentioning data acquisition).
+What jobs require data acquisition?
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 data acquisition are Automation and Controls Engineer (31.4% of that role’s postings mention data acquisition), Integration & Test Engineer (27.6% of that role’s postings mention data acquisition), Environmental Test Engineer (25.0% of that role’s postings mention data acquisition).
+What skills are commonly paired with data acquisition?
Across job postings indexed by Skillenai (90 days ending 2026-09-30), data acquisition most often appears alongside Python, MATLAB, Data analysis, test automation, instrumentation.
+Where is data acquisition most in demand?
As of 2026-09-30, the metro areas posting the most jobs requiring data acquisition are Long Beach, El Segundo, Costa Mesa, Lexington, Irvine, according to the Skillenai jobs index.
+How can I keep up with new data acquisition content and jobs?
Skillenai indexes news, blog posts, and research papers mentioning data acquisition alongside the jobs index. You can subscribe to a daily email digest of new data acquisition content from your Skillenai account.
+Which skills come before and after data acquisition?
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 acquisition — last 90 days
Salary distribution
Box = 25th–75th percentile · tick = median · whisker = 10th–90th · USD, annualized
Career paths around data acquisition
Skills documented before and after this skill across employer changes.
Historical career profiles · all locations
Skills before data acquisition
Skills after data acquisition
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: spark | 2 |
| Before: python | 2 |
| Before: AWS | 2 |
| Before: Tableau | 2 |
| Before: fraud detection | 2 |
| Before: snowflake | 2 |
| Before: Kafka | 2 |
| Before: NLP | 1 |
| After: DynamoDB | 2 |
| After: exploratory data analysis (EDA) | 2 |
| After: ETL | 2 |
| After: CSS | 2 |
| After: SQL Server | 2 |
| After: Algorithm | 1 |
| After: C# | 1 |
| After: facial recognition | 1 |
Roles most likely to require data acquisition
Among roles with at least 20 postings in the same period.
| Role | Postings mentioning skill | % of role postings mentioning skill |
|---|---|---|
| Automation and Controls Engineer | 11 | 31.4% |
| Integration & Test Engineer | 8 | 27.6% |
| Environmental Test Engineer | 6 | 25.0% |
| Electrical Test Engineer | 12 | 21.1% |
| Product Test Engineer | 5 | 17.9% |
| Propulsion Test Engineer | 4 | 17.4% |
| Mechanical Test Engineer | 5 | 17.2% |
| Manufacturing Test Engineer | 14 | 15.6% |
| Avionics Test Engineer | 3 | 11.5% |
| Hardware Test Engineer | 9 | 11.1% |
Roles with the most data acquisition postings
| Role | Postings mentioning skill | Share of skill postings |
|---|---|---|
| Test Engineer | 57 | 10.9% |
| Software Engineer | 21 | 4.0% |
| Data Scientist | 20 | 3.8% |
| Data Engineer | 17 | 3.3% |
| Manufacturing Test Engineer | 14 | 2.7% |
| Systems Engineer | 13 | 2.5% |
| Electrical Test Engineer | 12 | 2.3% |
| Automation and Controls Engineer | 11 | 2.1% |
| Automation Engineer | 10 | 1.9% |
| Product Manager | 10 | 1.9% |
Top companies posting jobs requiring data acquisition
Employers ranked by indexed job postings in the last 90 days.
| Company | Postings · 90 days |
|---|---|
| Anduril Industries | 46 |
| Anduril | 25 |
| SpaceX | 25 |
| Varda Space Industries | 25 |
| Northrop Grumman | 10 |
| Relativity Space | 9 |
| True Anomaly | 8 |
| ProSidian Consulting | 7 |
| Sentilink | 7 |
| Form Energy | 6 |
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 acquisition
| Name | Postings | Share |
|---|---|---|
| Long Beach | 30 | 5.7% |
| El Segundo | 28 | 5.4% |
| Costa Mesa | 19 | 3.6% |
| Lexington | 18 | 3.4% |
| Irvine | 16 | 3.1% |
| Los Angeles | 13 | 2.5% |
| McGregor | 9 | 1.7% |
| Singapore | 9 | 1.7% |
| San Francisco | 8 | 1.5% |
Skills commonly paired with data acquisition
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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 data acquisition by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s data acquisition postings by all data acquisition 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 2,595 identified employers and covers 68% of earlier and 72% of latest indexed postings. Windows: 2026-06-02 to 2026-08-31 and 2026-06-30 to 2026-09-28 (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
- 3260d452ef3a73a0
- 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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