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

As of 2026-10-13, distributed data processing appears in 293 job postings indexed by Skillenai over the past 90 days — Data Engineer has the most postings mentioning distributed data processing, with demand share up 0.6% vs the prior 4 weeks.

Last updated · 90d ending 2026-10-13

Postings · last 90 days
293
Demand vs prior month
up 0.6% vs the prior 4 weeks
Top role · 37.5% of skill postings
Data Engineer
Top hiring metro
London

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Frequently asked questions about distributed data processing

+Is distributed data processing in demand in 2026?

Yes. distributed data processing appears in 293 job postings indexed by Skillenai over the 90 days ending 2026-10-13. Data Engineer accounts for the most postings mentioning distributed data processing (37.5% of all postings mentioning distributed data processing).

+What jobs require distributed data processing?

According to the Skillenai jobs index over the 90 days ending 2026-10-13, among roles with at least 20 postings, the highest shares mentioning distributed data processing are AI/ML Scientist (14.3% of that role’s postings mention distributed data processing), Machine Learning Research Engineer (5.6% of that role’s postings mention distributed data processing), Senior Data Engineer (5.6% of that role’s postings mention distributed data processing).

+What skills are commonly paired with distributed data processing?

Across job postings indexed by Skillenai (90 days ending 2026-10-13), distributed data processing most often appears alongside Python, SQL, AWS, ETL, Databricks.

+Where is distributed data processing most in demand?

As of 2026-10-13, the metro areas posting the most jobs requiring distributed data processing are London, New York City, San Francisco, Bengaluru, Seattle, according to the Skillenai jobs index.

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

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

+Which skills come before and after distributed data processing?

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 distributed data processing — last 90 days

Career paths around distributed data processing

Skills documented before and after this skill across employer changes.

Historical career profiles · all locations

Skills before distributed data processing

Before distributed data processingMYSQL → distributed data processing: 1 observed employer moves with this skill pairJava 8 → distributed data processing: 1 observed employer moves with this skill pairHighcharts → distributed data processing: 1 observed employer moves with this skill pairMultithreading → distributed data processing: 1 observed employer moves with this skill pairApache Solr → distributed data processing: 1 observed employer moves with this skill pairBootstrap → distributed data processing: 1 observed employer moves with this skill pairApache Tika → distributed data processing: 1 observed employer moves with this skill pairHamming code → distributed data processing: 1 observed employer moves with this skill pairdistributeddataprocessingMYSQL: 1 movesMYSQL1 movesJava 8: 1 movesJava 81 movesHighcharts: 1 movesHighcharts1 movesMultithreading: 1 movesMultithreading1 movesApache Solr: 1 movesApache Solr1 movesBootstrap: 1 movesBootstrap1 movesApache Tika: 1 movesApache Tika1 movesHamming code: 1 movesHamming code1 moves

Skills after distributed data processing

After distributed data processingdistributed data processing → machine learning algorithms: 1 observed employer moves with this skill pairdistributed data processing → reliability: 1 observed employer moves with this skill pairdistributed data processing → Agile processes: 1 observed employer moves with this skill pairdistributed data processing → threat detection capabilities: 1 observed employer moves with this skill pairdistributed data processing → cybersecurity solutions: 1 observed employer moves with this skill pairdistributed data processing → cloud based systems: 1 observed employer moves with this skill pairdistributed data processing → Azure Active Directory: 1 observed employer moves with this skill pairdistributed data processing → Azure Data Lake: 1 observed employer moves with this skill pairdistributeddataprocessingmachine learning algorithms: 1 movesmachine learningalgorithms1 movesreliability: 1 movesreliability1 movesAgile processes: 1 movesAgile processes1 movesthreat detection capabilities: 1 movesthreat detectioncapabilities1 movescybersecurity solutions: 1 movescybersecuritysolutions1 movescloud based systems: 1 movescloud basedsystems1 movesAzure Active Directory: 1 movesAzure ActiveDirectory1 movesAzure Data Lake: 1 movesAzure Data Lake1 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: MYSQL1
Before: Java 81
Before: Highcharts1
Before: Multithreading1
Before: Apache Solr1
Before: Bootstrap1
Before: Apache Tika1
Before: Hamming code1
After: machine learning algorithms1
After: reliability1
After: Agile processes1
After: threat detection capabilities1
After: cybersecurity solutions1
After: cloud based systems1
After: Azure Active Directory1
After: Azure Data Lake1

Roles most likely to require distributed data processing

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

RolePostings mentioning skill% of role postings mentioning skill
AI/ML Scientist314.3%
Machine Learning Research Engineer25.6%
Senior Data Engineer25.6%
Lead Data Engineer45.0%
Applied Scientist83.3%
Data Engineering Director22.9%
Technical Lead Manager12.9%
Data Infrastructure Engineer12.9%
Information Technology Specialist12.7%
Chief Architect12.3%

Roles with the most distributed data processing postings

RolePostings mentioning skillShare of skill postings
Data Engineer11037.5%
Software Engineer4314.7%
Data Scientist3110.6%
Machine Learning Engineer165.5%
Applied Scientist82.7%
Backend Engineer41.4%
Lead Data Engineer41.4%
Research Engineer41.4%
AI Engineer31.0%
AI/ML Scientist31.0%

Top companies posting jobs requiring distributed data processing

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

Top companies posting jobs requiring distributed data processing
CompanyPostings · 90 days
Mastercard12
Celonis11
Barclays8
Cisco8
Wayve7
Zeta Global6
Vanguard6
ASOS6
Spotify4
General Motors4

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 distributed data processing

NamePostingsShare
London134.4%
New York City124.1%
San Francisco82.7%
Bengaluru62.0%
Seattle62.0%
Copenhagen51.7%
Warsaw51.7%
Berlin41.4%
Hyderabad41.4%

Skills commonly paired with distributed data processing

Python (205)SQL (163)AWS (88)ETL (85)Databricks (84)Spark (77)data pipelines (74)CI/CD (71)data modeling (71)Apache Spark (69)

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How this was computed

Counts derive from the Skillenai jobs index over the 90 days ending 2026-10-13. 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 distributed data processing by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s distributed data processing postings by all distributed data processing 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 2,615 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
a39e068217c09565
data_as_of
2026-10-13
window_days
90
Hiring engineers who use distributed data processing?

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Compiled by Jared Rand · Data sourced from the Skillenai labor market index