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

As of 2026-10-14, data flows appears in 536 job postings indexed by Skillenai over the past 90 days — Product Manager has the most postings mentioning data flows, with demand share up 6.4% vs the prior 4 weeks.

Last updated · 90d ending 2026-10-14

Postings · last 90 days
536
Demand vs prior month
up 6.4% vs the prior 4 weeks
Top role · 20.1% of skill postings
Top hiring metro
San Francisco

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Frequently asked questions about data flows

+Is data flows in demand in 2026?

Yes. data flows appears in 536 job postings indexed by Skillenai over the 90 days ending 2026-10-14. Product Manager accounts for the most postings mentioning data flows (20.1% of all postings mentioning data flows).

+What jobs require data flows?

According to the Skillenai jobs index over the 90 days ending 2026-10-14, among roles with at least 20 postings, the highest shares mentioning data flows are Technical Business Analyst (6.4% of that role’s postings mention data flows), AI Deployment Engineer (5.4% of that role’s postings mention data flows), Delivery Manager (5.0% of that role’s postings mention data flows).

+What skills are commonly paired with data flows?

Across job postings indexed by Skillenai (90 days ending 2026-10-14), data flows most often appears alongside APIs, Integrations, SQL, Agile, Product Management.

+Where is data flows most in demand?

As of 2026-10-14, the metro areas posting the most jobs requiring data flows are San Francisco, New York City, London, Seattle, Toronto, according to the Skillenai jobs index.

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

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

+Which skills come before and after data flows?

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 flows — last 90 days

Salary distribution

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

Career paths around data flows

Skills documented before and after this skill across employer changes.

Historical career profiles · all locations

Skills before data flows

Before data flowspython → data flows: 5 observed employer moves with this skill pairETL → data flows: 4 observed employer moves with this skill pairsql → data flows: 4 observed employer moves with this skill pairTableau → data flows: 4 observed employer moves with this skill pairJira → data flows: 3 observed employer moves with this skill pairuser stories → data flows: 3 observed employer moves with this skill pairtest cases → data flows: 2 observed employer moves with this skill pairC# → data flows: 2 observed employer moves with this skill pairdata flowspython: 5 movespython5 movesETL: 4 movesETL4 movessql: 4 movessql4 movesTableau: 4 movesTableau4 movesJira: 3 movesJira3 movesuser stories: 3 movesuser stories3 movestest cases: 2 movestest cases2 movesC#: 2 movesC#2 moves

Skills after data flows

After data flowsdata flows → Excel: 2 observed employer moves with this skill pairdata flows → Redshift: 2 observed employer moves with this skill pairdata flows → interviews: 2 observed employer moves with this skill pairdata flows → data pipelines: 2 observed employer moves with this skill pairdata flows → Azure Data Factory: 2 observed employer moves with this skill pairdata flows → user stories: 2 observed employer moves with this skill pairdata flows → Data ingestion: 2 observed employer moves with this skill pairdata flows → spark: 2 observed employer moves with this skill pairdata flowsExcel: 2 movesExcel2 movesRedshift: 2 movesRedshift2 movesinterviews: 2 movesinterviews2 movesdata pipelines: 2 movesdata pipelines2 movesAzure Data Factory: 2 movesAzure Data Factory2 movesuser stories: 2 movesuser stories2 movesData ingestion: 2 movesData ingestion2 movesspark: 2 movesspark2 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: python5
Before: ETL4
Before: sql4
Before: Tableau4
Before: Jira3
Before: user stories3
Before: test cases2
Before: C#2
After: Excel2
After: Redshift2
After: interviews2
After: data pipelines2
After: Azure Data Factory2
After: user stories2
After: Data ingestion2
After: spark2

Roles most likely to require data flows

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

RolePostings mentioning skill% of role postings mentioning skill
Technical Business Analyst106.4%
AI Deployment Engineer25.4%
Delivery Manager15.0%
Power Platform Developer15.0%
Technical Solution Architect15.0%
Business Systems Architect14.8%
Solution Consultant14.2%
Security Solutions Architect13.8%
Engineering Team Lead13.6%
People Analytics Manager13.3%

Roles with the most data flows postings

RolePostings mentioning skillShare of skill postings
Product Manager10820.1%
Business Analyst397.3%
Technical Product Manager305.6%
Software Engineer295.4%
Technical Program Manager275.0%
Solution Architect244.5%
Product Owner152.8%
Solutions Architect122.2%
Technical Business Analyst101.9%
AI Deployment Consultant61.1%

Top companies posting jobs requiring data flows

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

Top companies posting jobs requiring data flows
CompanyPostings · 90 days
Sezzle9
Expedia Group8
Capco8
OpenAI7
ING6
ServiceNow6
Intercom5
Gusto4
Mastercard4
Northrop Grumman4

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 flows

NamePostingsShare
San Francisco264.9%
New York City244.5%
London132.4%
Seattle112.1%
Toronto101.9%
Pune91.7%
Sydney81.5%
Bengaluru61.1%
Berlin61.1%

Skills commonly paired with data flows

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How this was computed

Counts derive from the Skillenai jobs index over the 90 days ending 2026-10-14. 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 flows by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s data flows postings by all data flows 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: 0.2% to 0.2%. 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 2,614 identified employers and covers 71% of earlier and 72% of latest indexed postings. Windows: 2026-06-16 to 2026-09-14 and 2026-07-14 to 2026-10-12 (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
0e59bb83da34ba37
data_as_of
2026-10-14
window_days
90
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Compiled by Jared Rand · Data sourced from the Skillenai labor market index