Redshift jobs in 2026 — demand, top roles hiring, and related skills

As of 2026-10-29, Redshift appears in 1,199 job postings indexed by Skillenai over the past 90 days — Data Engineer has the most postings mentioning Redshift, with demand share up 2.5% vs the prior 4 weeks.

Last updated · 90d ending 2026-10-29

Postings · last 90 days
1,199
Demand vs prior month
up 2.5% vs the prior 4 weeks
Top role · 33.5% of skill postings
Top hiring metro
New York City

Which roles want Redshift?

Upload your resume and Skillenai will show which roles your Redshift experience fits, which skills you already cover, and what is missing.

Frequently asked questions about Redshift

+Is Redshift in demand in 2026?

Yes. Redshift appears in 1,199 job postings indexed by Skillenai over the 90 days ending 2026-10-29. Data Engineer accounts for the most postings mentioning Redshift (33.5% of all postings mentioning Redshift).

+What jobs require Redshift?

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 Redshift are Customer Reliability Engineer (19.0% of that role’s postings mention Redshift), Back-End Developer (16.1% of that role’s postings mention Redshift), Data Infrastructure Engineer (12.1% of that role’s postings mention Redshift).

+What skills are commonly paired with Redshift?

Across job postings indexed by Skillenai (90 days ending 2026-10-29), Redshift most often appears alongside Python, SQL, Snowflake, AWS, BigQuery.

+Where is Redshift most in demand?

As of 2026-10-29, 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

Before Redshiftpython → Redshift: 143 observed employer moves with this skill pairsql → Redshift: 105 observed employer moves with this skill pairTableau → Redshift: 82 observed employer moves with this skill pairPower BI → Redshift: 77 observed employer moves with this skill pairPySpark → Redshift: 77 observed employer moves with this skill pairsnowflake → Redshift: 68 observed employer moves with this skill pairspark → Redshift: 66 observed employer moves with this skill pairKafka → Redshift: 65 observed employer moves with this skill pairRedshiftpython: 143 movespython143 movessql: 105 movessql105 movesTableau: 82 movesTableau82 movesPower BI: 77 movesPower BI77 movesPySpark: 77 movesPySpark77 movessnowflake: 68 movessnowflake68 movesspark: 66 movesspark66 movesKafka: 65 movesKafka65 moves

Skills after Redshift

After RedshiftRedshift → snowflake: 55 observed employer moves with this skill pairRedshift → databricks: 55 observed employer moves with this skill pairRedshift → Power BI: 51 observed employer moves with this skill pairRedshift → python: 51 observed employer moves with this skill pairRedshift → Azure Data Factory: 49 observed employer moves with this skill pairRedshift → PySpark: 48 observed employer moves with this skill pairRedshift → Kafka: 38 observed employer moves with this skill pairRedshift → airflow: 36 observed employer moves with this skill pairRedshiftsnowflake: 55 movessnowflake55 movesdatabricks: 55 movesdatabricks55 movesPower BI: 51 movesPower BI51 movespython: 51 movespython51 movesAzure Data Factory: 49 movesAzure Data Factory49 movesPySpark: 48 movesPySpark48 movesKafka: 38 movesKafka38 movesairflow: 36 movesairflow36 moves
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.

Observed connections and move counts
ConnectionMoves
Before: python143
Before: sql105
Before: Tableau82
Before: Power BI77
Before: PySpark77
Before: snowflake68
Before: spark66
Before: Kafka65
After: snowflake55
After: databricks55
After: Power BI51
After: python51
After: Azure Data Factory49
After: PySpark48
After: Kafka38
After: airflow36

Roles most likely to require Redshift

Among roles with at least 20 postings in the same period.

RolePostings mentioning skill% of role postings mentioning skill
Customer Reliability Engineer419.0%
Back-End Developer516.1%
Data Infrastructure Engineer412.1%
BI Engineer510.4%
Data Engineering Manager239.5%
Analytics Developer29.5%
Analytics Engineering Director29.1%
Lead Architect29.1%
Analytics Engineer719.0%
Business Intelligence Engineer88.5%

Roles with the most Redshift postings

RolePostings mentioning skillShare of skill postings
Data Engineer40233.5%
Software Engineer12410.3%
Analytics Engineer715.9%
Data Analyst584.8%
Data Scientist342.8%
Solutions Architect292.4%
Data Engineering Manager231.9%
Data Architect211.8%
Data Platform Engineer161.3%
Backend Engineer151.3%

Top companies posting jobs requiring Redshift

Employers ranked by indexed job postings in the last 90 days.

Top companies posting jobs requiring Redshift
CompanyPostings · 90 days
Capital One103
Databricks12
Amazon10
Sixt10
Disney9
Sentilink9
Stripe9
Sezzle9
Baytech Consulting9
Remote9

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

NamePostingsShare
New York City443.7%
San Francisco413.4%
Bengaluru312.6%
Hyderabad302.5%
Chicago161.3%
Pune151.3%
Long Beach121.0%
Seattle121.0%
McLean110.9%

Skills commonly paired with Redshift

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 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: 0.4% to 0.4%. 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
b47cbf80299e961c
data_as_of
2026-10-29
window_days
90
Compiled by Jared Rand · Data sourced from the Skillenai labor market index