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

As of 2026-09-30, data aggregation appears in 186 job postings indexed by Skillenai over the past 90 days — Data Scientist has the most postings mentioning data aggregation, with demand share up 6.0% vs the prior 4 weeks.

Last updated · 90d ending 2026-09-30

Postings · last 90 days
186
Demand vs prior month
up 6.0% vs the prior 4 weeks
Top role · 18.3% of skill postings
Top hiring metro
Toronto

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Frequently asked questions about data aggregation

+Is data aggregation in demand in 2026?

Yes. data aggregation appears in 186 job postings indexed by Skillenai over the 90 days ending 2026-09-30. Data Scientist accounts for the most postings mentioning data aggregation (18.3% of all postings mentioning data aggregation).

+What jobs require data aggregation?

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 data aggregation are Credit Risk Analyst (7.1% of that role’s postings mention data aggregation), Data Analytics Analyst (5.0% of that role’s postings mention data aggregation), Business Analyst Intern (4.8% of that role’s postings mention data aggregation).

+What skills are commonly paired with data aggregation?

Across job postings indexed by Skillenai (90 days ending 2026-09-30), data aggregation most often appears alongside SQL, Python, data visualization, Data analysis, data modeling.

+Where is data aggregation most in demand?

As of 2026-09-30, the metro areas posting the most jobs requiring data aggregation are Toronto, New York City, Washington, Bengaluru, Boston, according to the Skillenai jobs index.

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

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

+Which skills come before and after data aggregation?

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 aggregation — last 90 days

Career paths around data aggregation

Skills documented before and after this skill across employer changes.

Historical career profiles · all locations

Skills before data aggregation

Before data aggregationsql → data aggregation: 5 observed employer moves with this skill pairExcel → data aggregation: 2 observed employer moves with this skill pairdata analysis → data aggregation: 2 observed employer moves with this skill pairTableau → data aggregation: 2 observed employer moves with this skill pairUI → data aggregation: 2 observed employer moves with this skill pairarchitectural overhaul → data aggregation: 1 observed employer moves with this skill pairSQL DB → data aggregation: 1 observed employer moves with this skill pairKYC/AML → data aggregation: 1 observed employer moves with this skill pairdataaggregationsql: 5 movessql5 movesExcel: 2 movesExcel2 movesdata analysis: 2 movesdata analysis2 movesTableau: 2 movesTableau2 movesUI: 2 movesUI2 movesarchitectural overhaul: 1 movesarchitecturaloverhaul1 movesSQL DB: 1 movesSQL DB1 movesKYC/AML: 1 movesKYC/AML1 moves

Skills after data aggregation

After data aggregationdata aggregation → Tableau: 3 observed employer moves with this skill pairdata aggregation → sql: 3 observed employer moves with this skill pairdata aggregation → data cleansing: 2 observed employer moves with this skill pairdata aggregation → python: 2 observed employer moves with this skill pairdata aggregation → data validation: 2 observed employer moves with this skill pairdata aggregation → Power BI: 2 observed employer moves with this skill pairdata aggregation → ETL: 2 observed employer moves with this skill pairdata aggregation → KPI reporting: 1 observed employer moves with this skill pairdataaggregationTableau: 3 movesTableau3 movessql: 3 movessql3 movesdata cleansing: 2 movesdata cleansing2 movespython: 2 movespython2 movesdata validation: 2 movesdata validation2 movesPower BI: 2 movesPower BI2 movesETL: 2 movesETL2 movesKPI reporting: 1 movesKPI reporting1 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: sql5
Before: Excel2
Before: data analysis2
Before: Tableau2
Before: UI2
Before: architectural overhaul1
Before: SQL DB1
Before: KYC/AML1
After: Tableau3
After: sql3
After: data cleansing2
After: python2
After: data validation2
After: Power BI2
After: ETL2
After: KPI reporting1

Roles most likely to require data aggregation

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

RolePostings mentioning skill% of role postings mentioning skill
Credit Risk Analyst27.1%
Data Analytics Analyst15.0%
Business Analyst Intern14.8%
Marketing Analytics Lead14.8%
Solutions Analyst14.8%
Data Business Analyst14.2%
Senior Data Scientist13.7%
Business Data Analyst32.9%
Assistant Program Manager12.8%
Data Engineering Intern12.7%

Roles with the most data aggregation postings

RolePostings mentioning skillShare of skill postings
Data Scientist3418.3%
Software Engineer137.0%
Data Analyst126.5%
Data Engineer105.4%
Product Manager84.3%
Business Analyst42.2%
Integration Reliability Engineer42.2%
Risk Analytics Consultant42.2%
Business Data Analyst31.6%
Data Science Manager31.6%

Top companies posting jobs requiring data aggregation

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

Top companies posting jobs requiring data aggregation
CompanyPostings · 90 days
NielsenIQ14
Lyft8
Stripe6
ProSidian Consulting3
360 IT Professionals3
Wf3
Mastercard3
Rakuten3
JPMorgan Chase & Co.3
Renesas2

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 aggregation

NamePostingsShare
Toronto115.9%
New York City105.4%
Washington63.2%
Bengaluru52.7%
Boston52.7%
Warsaw42.2%
Denver31.6%
London31.6%
Seattle31.6%

Skills commonly paired with data aggregation

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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 data aggregation by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s data aggregation postings by all data aggregation 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
746716a24af7fa59
data_as_of
2026-09-30
window_days
90
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Compiled by Jared Rand · Data sourced from the Skillenai labor market index