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

As of 2026-09-30, Dask appears in 148 job postings indexed by Skillenai over the past 90 days — Machine Learning Engineer has the most postings mentioning Dask, with demand share down 11.5% vs the prior 4 weeks.

Last updated · 90d ending 2026-09-30

Postings · last 90 days
148
Demand vs prior month
down 11.5% vs the prior 4 weeks
Top role · 27.0% of skill postings
Top hiring metro
New York City

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Frequently asked questions about Dask

+Is Dask in demand in 2026?

Yes. Dask appears in 148 job postings indexed by Skillenai over the 90 days ending 2026-09-30. Machine Learning Engineer accounts for the most postings mentioning Dask (27.0% of all postings mentioning Dask).

+What jobs require Dask?

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 Dask are ML Systems Engineer (9.8% of that role’s postings mention Dask), Data Infrastructure Engineer (6.9% of that role’s postings mention Dask), Machine Learning Research Engineer (5.9% of that role’s postings mention Dask).

+What skills are commonly paired with Dask?

Across job postings indexed by Skillenai (90 days ending 2026-09-30), Dask most often appears alongside Python, Spark, AWS, PyTorch, SQL.

+Where is Dask most in demand?

As of 2026-09-30, the metro areas posting the most jobs requiring Dask are New York City, San Francisco, London, Sydney, McLean, according to the Skillenai jobs index.

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

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

+Which skills come before and after Dask?

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 Dask — last 90 days

Career paths around Dask

Skills documented before and after this skill across employer changes.

Historical career profiles · all locations

Skills before Dask

Before Daskpython → Dask: 9 observed employer moves with this skill pairdocker → Dask: 5 observed employer moves with this skill pairApache Airflow → Dask: 5 observed employer moves with this skill pairkubernetes → Dask: 4 observed employer moves with this skill pairtensorflow → Dask: 4 observed employer moves with this skill pairpandas → Dask: 4 observed employer moves with this skill pairpytorch → Dask: 4 observed employer moves with this skill pairscikit-learn → Dask: 3 observed employer moves with this skill pairDaskpython: 9 movespython9 movesdocker: 5 movesdocker5 movesApache Airflow: 5 movesApache Airflow5 moveskubernetes: 4 moveskubernetes4 movestensorflow: 4 movestensorflow4 movespandas: 4 movespandas4 movespytorch: 4 movespytorch4 movesscikit-learn: 3 movesscikit-learn3 moves

Skills after Dask

After DaskDask → Decision Trees: 4 observed employer moves with this skill pairDask → pandas: 4 observed employer moves with this skill pairDask → spacy: 3 observed employer moves with this skill pairDask → ETL: 2 observed employer moves with this skill pairDask → numpy: 2 observed employer moves with this skill pairDask → pytorch: 2 observed employer moves with this skill pairDask → logistic regression: 2 observed employer moves with this skill pairDask → Tableau: 2 observed employer moves with this skill pairDaskDecision Trees: 4 movesDecision Trees4 movespandas: 4 movespandas4 movesspacy: 3 movesspacy3 movesETL: 2 movesETL2 movesnumpy: 2 movesnumpy2 movespytorch: 2 movespytorch2 moveslogistic regression: 2 moveslogisticregression2 movesTableau: 2 movesTableau2 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: python9
Before: docker5
Before: Apache Airflow5
Before: kubernetes4
Before: tensorflow4
Before: pandas4
Before: pytorch4
Before: scikit-learn3
After: Decision Trees4
After: pandas4
After: spacy3
After: ETL2
After: numpy2
After: pytorch2
After: logistic regression2
After: Tableau2

Roles most likely to require Dask

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

RolePostings mentioning skill% of role postings mentioning skill
ML Systems Engineer49.8%
Data Infrastructure Engineer26.9%
Machine Learning Research Engineer25.9%
AI/ML Architect13.8%
Machine Learning Systems Engineer13.7%
Senior Data Engineer12.8%
ML Ops Engineer12.4%
Quantitative Developer22.4%
Machine Learning Engineer401.7%
AI Infrastructure Engineer11.4%

Roles with the most Dask postings

RolePostings mentioning skillShare of skill postings
Machine Learning Engineer4027.0%
Data Engineer2013.5%
Software Engineer1610.8%
Data Scientist1510.1%
ML Engineer64.1%
ML Systems Engineer42.7%
Applied Engineer32.0%
Cloud AI Engineer21.4%
Cloud Infrastructure Engineer21.4%
Data Infrastructure Engineer21.4%

Top companies posting jobs requiring Dask

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

Top companies posting jobs requiring Dask
CompanyPostings · 90 days
Capital One30
Xero10
PhysicsX7
Varicent6
Devoteam4
Sana Commerce4
Viber3
Affirm3
JDA3
ABOUT YOU SE & Co. KG3

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 Dask

NamePostingsShare
New York City149.5%
San Francisco74.7%
London64.1%
Sydney64.1%
McLean53.4%
Seattle42.7%
Bengaluru32.0%
Berlin32.0%
Madrid32.0%

Skills commonly paired with Dask

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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 Dask by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s Dask postings by all Dask 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
1a64d89c4ab0a6a4
data_as_of
2026-09-30
window_days
90
Hiring engineers who use Dask?

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