Redshift jobs in 2026 — demand, top roles hiring, and related skills
As of 2026-09-30, Redshift appears in 1,055 job postings indexed by Skillenai over the past 90 days — Data Engineer has the most postings mentioning Redshift, with demand share down 0.9% vs the prior 4 weeks.
Last updated · 90d ending 2026-09-30
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Frequently asked questions about Redshift
+Is Redshift in demand in 2026?
Yes. Redshift appears in 1,055 job postings indexed by Skillenai over the 90 days ending 2026-09-30. Data Engineer accounts for the most postings mentioning Redshift (30.9% of all postings mentioning Redshift).
+What jobs require Redshift?
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 Redshift are Customer Reliability Engineer (19.2% of that role’s postings mention Redshift), Data Consultant (12.5% of that role’s postings mention Redshift), Lead Architect (11.5% of that role’s postings mention Redshift).
+What skills are commonly paired with Redshift?
Across job postings indexed by Skillenai (90 days ending 2026-09-30), Redshift most often appears alongside Python, SQL, Snowflake, AWS, BigQuery.
+Where is Redshift most in demand?
As of 2026-09-30, the metro areas posting the most jobs requiring Redshift are New York City, San Francisco, Bengaluru, Hyderabad, Chicago, according to the Skillenai jobs index.
+How can I keep up with new Redshift content and jobs?
Skillenai indexes news, blog posts, and research papers mentioning Redshift alongside the jobs index. You can subscribe to a daily email digest of new Redshift content from your Skillenai account.
+Which skills come before and after Redshift?
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 Redshift — last 90 days
Salary distribution
Box = 25th–75th percentile · tick = median · whisker = 10th–90th · USD, annualized
Career paths around Redshift
Skills documented before and after this skill across employer changes.
Historical career profiles · all locations
Skills before Redshift
Skills after Redshift
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 | 133 |
| Before: sql | 92 |
| Before: Power BI | 74 |
| Before: PySpark | 72 |
| Before: Tableau | 71 |
| Before: snowflake | 65 |
| Before: spark | 63 |
| Before: Kafka | 63 |
| After: databricks | 54 |
| After: snowflake | 53 |
| After: Power BI | 50 |
| After: python | 49 |
| After: PySpark | 48 |
| After: Azure Data Factory | 48 |
| After: Kafka | 36 |
| After: spark | 35 |
Roles most likely to require Redshift
Among roles with at least 20 postings in the same period.
| Role | Postings mentioning skill | % of role postings mentioning skill |
|---|---|---|
| Customer Reliability Engineer | 5 | 19.2% |
| Data Consultant | 3 | 12.5% |
| Lead Architect | 3 | 11.5% |
| Finance Data Analyst | 3 | 11.1% |
| Data Infrastructure Engineer | 3 | 10.3% |
| Enterprise Solutions Architect | 2 | 10.0% |
| Analytics Developer | 2 | 9.5% |
| Customer Solutions Architect | 2 | 9.1% |
| Data Engineering Manager | 20 | 8.6% |
| Analytics Engineering Manager | 2 | 8.3% |
Roles with the most Redshift postings
| Role | Postings mentioning skill | Share of skill postings |
|---|---|---|
| Data Engineer | 326 | 30.9% |
| Software Engineer | 101 | 9.6% |
| Data Analyst | 54 | 5.1% |
| Analytics Engineer | 53 | 5.0% |
| Data Scientist | 30 | 2.8% |
| Solutions Architect | 21 | 2.0% |
| Data Engineering Manager | 20 | 1.9% |
| Backend Engineer | 19 | 1.8% |
| Data Platform Engineer | 16 | 1.5% |
| Engineering Manager | 14 | 1.3% |
Top companies posting jobs requiring Redshift
Employers ranked by indexed job postings in the last 90 days.
| Company | Postings · 90 days |
|---|---|
| Capital One | 76 |
| Stripe | 11 |
| Databricks | 10 |
| Barclays | 10 |
| Disney | 9 |
| Sentilink | 9 |
| Sixt | 9 |
| Sezzle | 9 |
| Fivetran | 9 |
| Baytech Consulting | 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 Redshift
| Name | Postings | Share |
|---|---|---|
| New York City | 58 | 5.5% |
| San Francisco | 30 | 2.8% |
| Bengaluru | 27 | 2.6% |
| Hyderabad | 22 | 2.1% |
| Chicago | 17 | 1.6% |
| London | 17 | 1.6% |
| Pune | 12 | 1.1% |
| Long Beach | 11 | 1.0% |
| Stockholm | 11 | 1.0% |
Skills commonly paired with Redshift
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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 Redshift by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s Redshift postings by all Redshift 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
- b47cbf80299e961c
- 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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