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

As of 2026-11-05, indexing appears in 812 job postings indexed by Skillenai over the past 90 days — Software Engineer has the most postings mentioning indexing, with demand share down 16.0% vs the prior 4 weeks.

Last updated · 90d ending 2026-11-05

Postings · last 90 days
812
Demand vs prior month
down 16.0% vs the prior 4 weeks
Top role · 28.6% of skill postings
Top hiring metro
San Francisco

Which roles want indexing?

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

Frequently asked questions about indexing

+Is indexing in demand in 2026?

Yes. indexing appears in 812 job postings indexed by Skillenai over the 90 days ending 2026-11-05. Software Engineer accounts for the most postings mentioning indexing (28.6% of all postings mentioning indexing).

+What jobs require indexing?

According to the Skillenai jobs index over the 90 days ending 2026-11-05, among roles with at least 20 postings, the highest shares mentioning indexing are Database Engineer (27.9% of that role’s postings mention indexing), Database Administrator (DBA) (25.0% of that role’s postings mention indexing), Database Architect (21.6% of that role’s postings mention indexing).

+What skills are commonly paired with indexing?

Across job postings indexed by Skillenai (90 days ending 2026-11-05), indexing most often appears alongside query optimization, SQL, Python, PostgreSQL, CI/CD.

+Where is indexing most in demand?

As of 2026-11-05, the metro areas posting the most jobs requiring indexing are San Francisco, New York City, Bengaluru, London, Berlin, according to the Skillenai jobs index.

+How can I keep up with new indexing content and jobs?

Skillenai indexes news, blog posts, and research papers mentioning indexing alongside the jobs index. You can subscribe to a daily email digest of new indexing content from your Skillenai account.

+Which skills come before and after indexing?

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 indexing — last 90 days

Salary distribution

Box = 25th–75th percentile · tick = median · whisker = 10th–90th · USD, annualized

Career paths around indexing

Skills documented before and after this skill across employer changes.

Historical career profiles · all locations

Skills before indexing

Before indexingpython → indexing: 26 observed employer moves with this skill pairsql → indexing: 21 observed employer moves with this skill pairPower BI → indexing: 20 observed employer moves with this skill pairPySpark → indexing: 14 observed employer moves with this skill pairSQL Server → indexing: 10 observed employer moves with this skill pairAzure Data Factory → indexing: 9 observed employer moves with this skill pairTableau → indexing: 9 observed employer moves with this skill pairHive → indexing: 8 observed employer moves with this skill pairindexingpython: 26 movespython26 movessql: 21 movessql21 movesPower BI: 20 movesPower BI20 movesPySpark: 14 movesPySpark14 movesSQL Server: 10 movesSQL Server10 movesAzure Data Factory: 9 movesAzure Data Factory9 movesTableau: 9 movesTableau9 movesHive: 8 movesHive8 moves

Skills after indexing

After indexingindexing → python: 12 observed employer moves with this skill pairindexing → PySpark: 11 observed employer moves with this skill pairindexing → JavaScript: 10 observed employer moves with this skill pairindexing → sql: 9 observed employer moves with this skill pairindexing → snowflake: 9 observed employer moves with this skill pairindexing → S3: 9 observed employer moves with this skill pairindexing → Kafka: 8 observed employer moves with this skill pairindexing → Azure Data Factory: 8 observed employer moves with this skill pairindexingpython: 12 movespython12 movesPySpark: 11 movesPySpark11 movesJavaScript: 10 movesJavaScript10 movessql: 9 movessql9 movessnowflake: 9 movessnowflake9 movesS3: 9 movesS39 movesKafka: 8 movesKafka8 movesAzure Data Factory: 8 movesAzure Data Factory8 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: python26
Before: sql21
Before: Power BI20
Before: PySpark14
Before: SQL Server10
Before: Azure Data Factory9
Before: Tableau9
Before: Hive8
After: python12
After: PySpark11
After: JavaScript10
After: sql9
After: snowflake9
After: S39
After: Kafka8
After: Azure Data Factory8

Roles most likely to require indexing

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

RolePostings mentioning skill% of role postings mentioning skill
Database Engineer3627.9%
Database Administrator (DBA)625.0%
Database Architect821.6%
Database Developer619.4%
Search Engineer312.0%
Database Administrator7311.4%
SEO Specialist510.2%
SQL Database Administrator29.5%
Data Infrastructure Engineer38.8%
Database Reliability Engineer37.3%

Roles with the most indexing postings

RolePostings mentioning skillShare of skill postings
Software Engineer23228.6%
Database Administrator739.0%
Data Engineer718.7%
Database Engineer364.4%
Backend Engineer222.7%
AI Engineer202.5%
Full Stack Engineer91.1%
Product Manager91.1%
Data Scientist81.0%
Database Architect81.0%

Top companies posting jobs requiring indexing

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

Top companies posting jobs requiring indexing
CompanyPostings · 90 days
Elastic19
Feverup12
Truelogic8
Gitlab8
WPP7
CLERA7
ABOUT YOU SE & Co. KG7
In All Media Inc7
Horizon3.ai6
OpenAI5

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 indexing

NamePostingsShare
San Francisco364.4%
New York City202.5%
Bengaluru172.1%
London162.0%
Berlin131.6%
Pune111.4%
Austin81.0%
Chicago81.0%
Lisbon81.0%

Skills commonly paired with indexing

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 2026-11-05. 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 indexing by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s indexing postings by all indexing 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 0.3%. 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 2,472 identified employers and covers 71% of earlier and 70% of latest indexed postings. Windows: 2026-07-07 to 2026-10-05 and 2026-08-04 to 2026-11-02 (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
0adfc57e103a95c2
data_as_of
2026-11-05
window_days
90
Compiled by Jared Rand · Data sourced from the Skillenai labor market index