Skillenai

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

As of 2026-10-20, data models appears in 1,181 job postings indexed by Skillenai over the past 90 days — Product Manager has the most postings mentioning data models, with demand share down 12.8% vs the prior 4 weeks.

Last updated · 90d ending 2026-10-20

Postings · last 90 days
1,181
Demand vs prior month
down 12.8% vs the prior 4 weeks
Top role · 15.8% of skill postings
Product Manager
Top hiring metro
San Francisco

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Frequently asked questions about data models

+Is data models in demand in 2026?

Yes. data models appears in 1,181 job postings indexed by Skillenai over the 90 days ending 2026-10-20. Product Manager accounts for the most postings mentioning data models (15.8% of all postings mentioning data models).

+What jobs require data models?

According to the Skillenai jobs index over the 90 days ending 2026-10-20, among roles with at least 20 postings, the highest shares mentioning data models are Agent Strategist (100.0% of that role’s postings mention data models), Deployment Engineer (23.7% of that role’s postings mention data models), Salesforce Business Analyst (12.5% of that role’s postings mention data models).

+What skills are commonly paired with data models?

Across job postings indexed by Skillenai (90 days ending 2026-10-20), data models most often appears alongside APIs, SQL, Python, data pipelines, dashboards.

+Where is data models most in demand?

As of 2026-10-20, the metro areas posting the most jobs requiring data models are San Francisco, New York City, London, Bengaluru, Toronto, according to the Skillenai jobs index.

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

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

+Which skills come before and after data models?

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 data models — last 90 days

Salary distribution

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

Career paths around data models

Skills documented before and after this skill across employer changes.

Historical career profiles · all locations

Skills before data models

Before data modelssql → data models: 39 observed employer moves with this skill pairpython → data models: 38 observed employer moves with this skill pairTableau → data models: 32 observed employer moves with this skill pairPower BI → data models: 28 observed employer moves with this skill pairdashboards → data models: 19 observed employer moves with this skill pairETL → data models: 16 observed employer moves with this skill pairExcel → data models: 16 observed employer moves with this skill pairSQL Server → data models: 12 observed employer moves with this skill pairdata modelssql: 39 movessql39 movespython: 38 movespython38 movesTableau: 32 movesTableau32 movesPower BI: 28 movesPower BI28 movesdashboards: 19 movesdashboards19 movesETL: 16 movesETL16 movesExcel: 16 movesExcel16 movesSQL Server: 12 movesSQL Server12 moves

Skills after data models

After data modelsdata models → python: 26 observed employer moves with this skill pairdata models → Power BI: 23 observed employer moves with this skill pairdata models → sql: 22 observed employer moves with this skill pairdata models → Tableau: 21 observed employer moves with this skill pairdata models → ETL: 15 observed employer moves with this skill pairdata models → snowflake: 14 observed employer moves with this skill pairdata models → Azure: 11 observed employer moves with this skill pairdata models → databricks: 10 observed employer moves with this skill pairdata modelspython: 26 movespython26 movesPower BI: 23 movesPower BI23 movessql: 22 movessql22 movesTableau: 21 movesTableau21 movesETL: 15 movesETL15 movessnowflake: 14 movessnowflake14 movesAzure: 11 movesAzure11 movesdatabricks: 10 movesdatabricks10 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: sql39
Before: python38
Before: Tableau32
Before: Power BI28
Before: dashboards19
Before: ETL16
Before: Excel16
Before: SQL Server12
After: python26
After: Power BI23
After: sql22
After: Tableau21
After: ETL15
After: snowflake14
After: Azure11
After: databricks10

Roles most likely to require data models

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

RolePostings mentioning skill% of role postings mentioning skill
Agent Strategist30100.0%
Deployment Engineer923.7%
Salesforce Business Analyst512.5%
Salesforce Solution Architect410.5%
Data Product Owner410.3%
Success Architect59.1%
Data Analytics Specialist26.9%
Data Engineer Intern26.7%
Data & AI Engineer26.2%
Platform Architect86.2%

Roles with the most data models postings

RolePostings mentioning skillShare of skill postings
Product Manager18715.8%
Software Engineer17014.4%
Data Engineer423.6%
Data Analyst353.0%
Agent Strategist302.5%
Technical Product Manager302.5%
Business Analyst282.4%
Solution Architect231.9%
Backend Engineer201.7%
Data Scientist181.5%

Top companies posting jobs requiring data models

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

Top companies posting jobs requiring data models
CompanyPostings · 90 days
Sierra25
CLERA24
Celonis21
Ebury17
Sezzle16
Stripe12
ServiceNow12
Klaviyo10
Salesforce9
Airkit9

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 data models

NamePostingsShare
San Francisco958.0%
New York City736.2%
London514.3%
Bengaluru242.0%
Toronto221.9%
Boston191.6%
Madrid151.3%
Hyderabad131.1%
Los Angeles100.8%

Skills commonly paired with data models

APIs (330)SQL (319)Python (290)data pipelines (209)dashboards (160)data governance (121)observability (119)TypeScript (112)Integrations (109)Distributed systems (105)

Explore related pages

How this was computed

Counts derive from the Skillenai jobs index over the 90 days ending 2026-10-20. 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 data models by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s data models postings by all data models 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: 0.6% 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 2,610 identified employers and covers 72% of earlier and 73% of latest indexed postings. Windows: 2026-06-23 to 2026-09-21 and 2026-07-21 to 2026-10-19 (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
dc7bf960afa88469
data_as_of
2026-10-20
window_days
90
Compiled by Jared Rand · Data sourced from the Skillenai labor market index