Skillenai

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

As of 2026-10-30, MapReduce appears in 228 job postings indexed by Skillenai over the past 90 days — Data Engineer has the most postings mentioning MapReduce.

Last updated · 90d ending 2026-10-30

Postings · last 90 days
228
Top role · 28.1% of skill postings
Data Engineer
Top hiring metro
Annapolis

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Frequently asked questions about MapReduce

+Is MapReduce in demand in 2026?

Yes. MapReduce appears in 228 job postings indexed by Skillenai over the 90 days ending 2026-10-30. Data Engineer accounts for the most postings mentioning MapReduce (28.1% of all postings mentioning MapReduce).

+What jobs require MapReduce?

According to the Skillenai jobs index over the 90 days ending 2026-10-30, among roles with at least 20 postings, the highest shares mentioning MapReduce are Quantitative Engineer (25.0% of that role’s postings mention MapReduce), Lead Data Engineer (9.6% of that role’s postings mention MapReduce), Data Science Lead (4.3% of that role’s postings mention MapReduce).

+What skills are commonly paired with MapReduce?

Across job postings indexed by Skillenai (90 days ending 2026-10-30), MapReduce most often appears alongside Hadoop, Python, Spark, Hive, Kafka.

+Where is MapReduce most in demand?

As of 2026-10-30, the metro areas posting the most jobs requiring MapReduce are Annapolis, New York City, Bengaluru, Chicago, McLean, according to the Skillenai jobs index.

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

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

+Which skills come before and after MapReduce?

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 MapReduce — last 90 days

Salary distribution

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

Career paths around MapReduce

Skills documented before and after this skill across employer changes.

Historical career profiles · all locations

Skills before MapReduce

Before MapReducepython → MapReduce: 40 observed employer moves with this skill pairHive → MapReduce: 25 observed employer moves with this skill pairsql → MapReduce: 19 observed employer moves with this skill pairHadoop → MapReduce: 19 observed employer moves with this skill pairspark → MapReduce: 18 observed employer moves with this skill pairsnowflake → MapReduce: 17 observed employer moves with this skill pairPySpark → MapReduce: 16 observed employer moves with this skill pairTableau → MapReduce: 16 observed employer moves with this skill pairMapReducepython: 40 movespython40 movesHive: 25 movesHive25 movessql: 19 movessql19 movesHadoop: 19 movesHadoop19 movesspark: 18 movesspark18 movessnowflake: 17 movessnowflake17 movesPySpark: 16 movesPySpark16 movesTableau: 16 movesTableau16 moves

Skills after MapReduce

After MapReduceMapReduce → sql: 21 observed employer moves with this skill pairMapReduce → PySpark: 20 observed employer moves with this skill pairMapReduce → Jenkins: 19 observed employer moves with this skill pairMapReduce → Kafka: 18 observed employer moves with this skill pairMapReduce → snowflake: 18 observed employer moves with this skill pairMapReduce → python: 17 observed employer moves with this skill pairMapReduce → Azure Data Factory: 17 observed employer moves with this skill pairMapReduce → Redshift: 16 observed employer moves with this skill pairMapReducesql: 21 movessql21 movesPySpark: 20 movesPySpark20 movesJenkins: 19 movesJenkins19 movesKafka: 18 movesKafka18 movessnowflake: 18 movessnowflake18 movespython: 17 movespython17 movesAzure Data Factory: 17 movesAzure Data Factory17 movesRedshift: 16 movesRedshift16 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: python40
Before: Hive25
Before: sql19
Before: Hadoop19
Before: spark18
Before: snowflake17
Before: PySpark16
Before: Tableau16
After: sql21
After: PySpark20
After: Jenkins19
After: Kafka18
After: snowflake18
After: python17
After: Azure Data Factory17
After: Redshift16

Roles most likely to require MapReduce

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

RolePostings mentioning skill% of role postings mentioning skill
Quantitative Engineer525.0%
Lead Data Engineer79.6%
Data Science Lead14.3%
Back-end Developer14.0%
Big Data Engineer12.3%
Application Architect21.7%
Cloud Software Engineer11.3%
Software Engineering Director11.1%
Data Engineer641.0%
Machine Learning Scientist10.7%

Roles with the most MapReduce postings

RolePostings mentioning skillShare of skill postings
Data Engineer6428.1%
Software Engineer6327.6%
Data Scientist3314.5%
Lead Data Engineer73.1%
Data Analyst62.6%
Quantitative Engineer52.2%
AI Engineer31.3%
DevOps Engineer31.3%
Application Architect20.9%
Capacity Planning Engineer20.9%

Top companies posting jobs requiring MapReduce

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

Top companies posting jobs requiring MapReduce
CompanyPostings · 90 days
Capital One51
Bah26
Captivation12
Nebius9
Ghr5
Cisco5
Google3
Captivation Software3
Visual Soft Inc3
LinkedIn3

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 MapReduce

NamePostingsShare
Annapolis229.6%
New York City93.9%
Bengaluru83.5%
Chicago62.6%
McLean52.2%
Springfield52.2%
Amsterdam41.8%
Arlington41.8%
Huntsville41.8%

Skills commonly paired with MapReduce

Hadoop (161)Python (158)Spark (136)Hive (127)Kafka (103)Java (102)SQL (98)NoSQL (82)EMR (81)AWS (78)

Explore related pages

How this was computed

Weekly job-count charts omit the incomplete current week (weeks start Monday, UTC). Totals include all postings in the stated window. Counts derive from the Skillenai jobs index over the 90 days ending 2026-10-30. 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 MapReduce by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s MapReduce postings by all MapReduce 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). An adjusted trend is not shown because comparable posting coverage is insufficient.

source
Skillenai jobs index, deduplicated daily
entity_id
36a4739f9298586d
data_as_of
2026-10-30
window_days
90
Compiled by Jared Rand · Data sourced from the Skillenai labor market index