Amazon S3 jobs in 2026 — demand, top roles hiring, and related skills
As of 2026-09-30, Amazon S3 appears in 1,198 job postings indexed by Skillenai over the past 90 days — Software Engineer has the most postings mentioning Amazon S3, with demand share down 2.7% vs the prior 4 weeks.
Last updated · 90d ending 2026-09-30
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Frequently asked questions about Amazon S3
+Is Amazon S3 in demand in 2026?
Yes. Amazon S3 appears in 1,198 job postings indexed by Skillenai over the 90 days ending 2026-09-30. Software Engineer accounts for the most postings mentioning Amazon S3 (24.0% of all postings mentioning Amazon S3).
+What jobs require Amazon S3?
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 Amazon S3 are Cloud Data Engineer (21.4% of that role’s postings mention Amazon S3), AWS Cloud Engineer (13.8% of that role’s postings mention Amazon S3), Senior Data Engineer (8.3% of that role’s postings mention Amazon S3).
+What skills are commonly paired with Amazon S3?
Across job postings indexed by Skillenai (90 days ending 2026-09-30), Amazon S3 most often appears alongside AWS Lambda, Python, AWS, SQL, AWS Glue.
+Where is Amazon S3 most in demand?
As of 2026-09-30, the metro areas posting the most jobs requiring Amazon S3 are Bengaluru, London, Pune, New York City, Hyderabad, according to the Skillenai jobs index.
+How can I keep up with new Amazon S3 content and jobs?
Skillenai indexes news, blog posts, and research papers mentioning Amazon S3 alongside the jobs index. You can subscribe to a daily email digest of new Amazon S3 content from your Skillenai account.
+Which skills come before and after Amazon S3?
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 Amazon S3 — last 90 days
Salary distribution
Box = 25th–75th percentile · tick = median · whisker = 10th–90th · USD, annualized
Career paths around Amazon S3
Skills documented before and after this skill across employer changes.
Historical career profiles · all locations
Skills before Amazon S3
Skills after Amazon S3
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: python | 26 |
| Before: sql | 19 |
| Before: PySpark | 11 |
| Before: Azure Data Factory | 10 |
| Before: docker | 9 |
| Before: Git | 9 |
| Before: Jenkins | 9 |
| Before: Java | 9 |
| After: python | 16 |
| After: AWS | 14 |
| After: S3 | 12 |
| After: snowflake | 12 |
| After: Kafka | 11 |
| After: sql | 11 |
| After: docker | 11 |
| After: Jenkins | 10 |
Roles most likely to require Amazon S3
Among roles with at least 20 postings in the same period.
| Role | Postings mentioning skill | % of role postings mentioning skill |
|---|---|---|
| Cloud Data Engineer | 12 | 21.4% |
| AWS Cloud Engineer | 4 | 13.8% |
| Senior Data Engineer | 3 | 8.3% |
| Engineering Lead | 7 | 6.0% |
| Python Developer | 4 | 5.7% |
| Data Engineering Lead | 4 | 5.6% |
| Big Data Engineer | 3 | 5.6% |
| Full Stack AI Engineer | 2 | 5.4% |
| Business Intelligence Engineer | 4 | 5.3% |
| Database Reliability Engineer | 2 | 5.3% |
Roles with the most Amazon S3 postings
| Role | Postings mentioning skill | Share of skill postings |
|---|---|---|
| Software Engineer | 288 | 24.0% |
| Data Engineer | 247 | 20.6% |
| DevOps Engineer | 41 | 3.4% |
| Full Stack Engineer | 20 | 1.7% |
| Platform Engineer | 17 | 1.4% |
| Backend Engineer | 15 | 1.3% |
| Data Platform Engineer | 15 | 1.3% |
| Data Analyst | 14 | 1.2% |
| Data Architect | 14 | 1.2% |
| Data Scientist | 14 | 1.2% |
Top companies posting jobs requiring Amazon S3
Employers ranked by indexed job postings in the last 90 days.
| Company | Postings · 90 days |
|---|---|
| Barclays | 30 |
| General Dynamics Information Technology | 19 |
| Experian | 18 |
| JPMorgan Chase & Co. | 12 |
| Quantiphi | 11 |
| Knowbe4 | 11 |
| Vanguard | 11 |
| Flock | 9 |
| Elsevier | 9 |
| MSD | 9 |
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 Amazon S3
| Name | Postings | Share |
|---|---|---|
| Bengaluru | 47 | 3.9% |
| London | 32 | 2.7% |
| Pune | 31 | 2.6% |
| New York City | 29 | 2.4% |
| Hyderabad | 26 | 2.2% |
| Boston | 17 | 1.4% |
| Austin | 16 | 1.3% |
| Toronto | 14 | 1.2% |
| São Paulo | 12 | 1.0% |
Skills commonly paired with Amazon S3
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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 Amazon S3 by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s Amazon S3 postings by all Amazon S3 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: 0.5% to 0.5%. 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 2,596 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
- dfd12199d5076a95
- 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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