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

As of 2026-09-30, structured data appears in 372 job postings indexed by Skillenai over the past 90 days — Data Scientist has the most postings mentioning structured data, with demand share up 2.4% vs the prior 4 weeks.

Last updated · 90d ending 2026-09-30

Postings · last 90 days
372
Demand vs prior month
up 2.4% vs the prior 4 weeks
Top role · 7.0% of skill postings
Top hiring metro
New York City

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Frequently asked questions about structured data

+Is structured data in demand in 2026?

Yes. structured data appears in 372 job postings indexed by Skillenai over the 90 days ending 2026-09-30. Data Scientist accounts for the most postings mentioning structured data (7.0% of all postings mentioning structured data).

+What jobs require structured data?

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 structured data are Data Scientist Intern (14.9% of that role’s postings mention structured data), Web Engineer (8.9% of that role’s postings mention structured data), Growth Engineer (6.8% of that role’s postings mention structured data).

+What skills are commonly paired with structured data?

Across job postings indexed by Skillenai (90 days ending 2026-09-30), structured data most often appears alongside unstructured data, Technical SEO, SEO, Python, Core Web Vitals.

+Where is structured data most in demand?

As of 2026-09-30, the metro areas posting the most jobs requiring structured data are New York City, San Francisco, Toronto, Austin, London, according to the Skillenai jobs index.

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

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

+Which skills come before and after structured data?

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 structured data — last 90 days

Salary distribution

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

Career paths around structured data

Skills documented before and after this skill across employer changes.

Historical career profiles · all locations

Skills before structured data

Before structured dataPower BI → structured data: 2 observed employer moves with this skill pairsql → structured data: 2 observed employer moves with this skill pairR → structured data: 2 observed employer moves with this skill pairSingle page applications → structured data: 1 observed employer moves with this skill pairbranding → structured data: 1 observed employer moves with this skill pairCorrelation → structured data: 1 observed employer moves with this skill pairspeed → structured data: 1 observed employer moves with this skill pairBig Data analysis → structured data: 1 observed employer moves with this skill pairstructureddataPower BI: 2 movesPower BI2 movessql: 2 movessql2 movesR: 2 movesR2 movesSingle page applications: 1 movesSingle pageapplications1 movesbranding: 1 movesbranding1 movesCorrelation: 1 movesCorrelation1 movesspeed: 1 movesspeed1 movesBig Data analysis: 1 movesBig Data analysis1 moves

Skills after structured data

After structured datastructured data → Data Lake: 3 observed employer moves with this skill pairstructured data → snowflake: 2 observed employer moves with this skill pairstructured data → data warehouse: 2 observed employer moves with this skill pairstructured data → AWS ECS: 1 observed employer moves with this skill pairstructured data → ETL: 1 observed employer moves with this skill pairstructured data → litigation: 1 observed employer moves with this skill pairstructured data → managed services: 1 observed employer moves with this skill pairstructured data → CONUS: 1 observed employer moves with this skill pairstructureddataData Lake: 3 movesData Lake3 movessnowflake: 2 movessnowflake2 movesdata warehouse: 2 movesdata warehouse2 movesAWS ECS: 1 movesAWS ECS1 movesETL: 1 movesETL1 moveslitigation: 1 moveslitigation1 movesmanaged services: 1 movesmanaged services1 movesCONUS: 1 movesCONUS1 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: Power BI2
Before: sql2
Before: R2
Before: Single page applications1
Before: branding1
Before: Correlation1
Before: speed1
Before: Big Data analysis1
After: Data Lake3
After: snowflake2
After: data warehouse2
After: AWS ECS1
After: ETL1
After: litigation1
After: managed services1
After: CONUS1

Roles most likely to require structured data

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

RolePostings mentioning skill% of role postings mentioning skill
Data Scientist Intern1314.9%
Web Engineer48.9%
Growth Engineer36.8%
Enterprise Solutions Architect15.0%
Growth Manager15.0%
Agent Engineer14.8%
Digital Product Owner14.5%
Quantitative Risk Analyst14.5%
AI Business Analyst14.3%
Quantitative Strategist14.3%

Roles with the most structured data postings

RolePostings mentioning skillShare of skill postings
Data Scientist267.0%
Product Manager225.9%
Data Engineer174.6%
SEO Strategist174.6%
Software Engineer143.8%
Data Scientist Intern133.5%
SEO Manager113.0%
Machine Learning Engineer102.7%
Technical SEO Lead102.7%
AI Engineer71.9%

Top companies posting jobs requiring structured data

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

Top companies posting jobs requiring structured data
CompanyPostings · 90 days
Feverup21
Bah13
Renesas5
AvePoint5
Anthropic5
Elastic5
Shift Technology5
Coursera5
Zip Security4
Mentimeter4

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 structured data

NamePostingsShare
New York City205.4%
San Francisco184.8%
Toronto133.5%
Austin102.7%
London102.7%
Bengaluru71.9%
Chicago51.3%
Madrid51.3%
Milan51.3%

Skills commonly paired with structured data

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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 structured data by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s structured data postings by all structured data 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: 0.1% to 0.1%. 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
c11b3aff1e3f99be
data_as_of
2026-09-30
window_days
90
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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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Compiled by Jared Rand · Data sourced from the Skillenai labor market index