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

As of 2026-09-30, Iceberg appears in 481 job postings indexed by Skillenai over the past 90 days — Software Engineer has the most postings mentioning Iceberg, with demand share down 5.9% vs the prior 4 weeks.

Last updated · 90d ending 2026-09-30

Postings · last 90 days
481
Demand vs prior month
down 5.9% vs the prior 4 weeks
Top role · 29.5% of skill postings
Top hiring metro
London

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Frequently asked questions about Iceberg

+Is Iceberg in demand in 2026?

Yes. Iceberg appears in 481 job postings indexed by Skillenai over the 90 days ending 2026-09-30. Software Engineer accounts for the most postings mentioning Iceberg (29.5% of all postings mentioning Iceberg).

+What jobs require Iceberg?

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 Iceberg are Machine Learning Platform Engineer (20.8% of that role’s postings mention Iceberg), Data Platform Architect (10.8% of that role’s postings mention Iceberg), Machine Learning Systems Engineer (7.4% of that role’s postings mention Iceberg).

+What skills are commonly paired with Iceberg?

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

+Where is Iceberg most in demand?

As of 2026-09-30, the metro areas posting the most jobs requiring Iceberg are London, New York City, San Francisco, Pune, Long Beach, according to the Skillenai jobs index.

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

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

+Which skills come before and after Iceberg?

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 Iceberg — last 90 days

Salary distribution

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

Career paths around Iceberg

Skills documented before and after this skill across employer changes.

Historical career profiles · all locations

Skills before Iceberg

Before Icebergspark → Iceberg: 4 observed employer moves with this skill pairETL → Iceberg: 2 observed employer moves with this skill pairsql → Iceberg: 2 observed employer moves with this skill pairApache Iceberg → Iceberg: 2 observed employer moves with this skill pairAzure Data Factory → Iceberg: 2 observed employer moves with this skill pairAWS S3 → Iceberg: 2 observed employer moves with this skill pairsnowflake → Iceberg: 2 observed employer moves with this skill pairKafka → Iceberg: 2 observed employer moves with this skill pairIcebergspark: 4 movesspark4 movesETL: 2 movesETL2 movessql: 2 movessql2 movesApache Iceberg: 2 movesApache Iceberg2 movesAzure Data Factory: 2 movesAzure Data Factory2 movesAWS S3: 2 movesAWS S32 movessnowflake: 2 movessnowflake2 movesKafka: 2 movesKafka2 moves

Skills after Iceberg

No published outgoing skill pairs yet.

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: spark4
Before: ETL2
Before: sql2
Before: Apache Iceberg2
Before: Azure Data Factory2
Before: AWS S32
Before: snowflake2
Before: Kafka2

Roles most likely to require Iceberg

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

RolePostings mentioning skill% of role postings mentioning skill
Machine Learning Platform Engineer520.8%
Data Platform Architect410.8%
Machine Learning Systems Engineer27.4%
Data Platform Engineer144.8%
Lead Data Engineer34.0%
Distributed Systems Engineer23.1%
Lead Data Scientist33.0%
Staff Software Engineer42.9%
Data Engineering Director22.8%
Data Engineering Lead22.8%

Roles with the most Iceberg postings

RolePostings mentioning skillShare of skill postings
Software Engineer14229.5%
Data Engineer11123.1%
Engineering Manager214.4%
Data Platform Engineer142.9%
R&D Software Engineer142.9%
Analytics Engineer61.2%
Data Engineering Manager51.0%
Graph Databases Director51.0%
ML Engineer51.0%
Machine Learning Platform Engineer51.0%

Top companies posting jobs requiring Iceberg

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

Top companies posting jobs requiring Iceberg
CompanyPostings · 90 days
Wise19
Stripe18
Fivetran17
Barclays14
CrowdStrike10
Klaviyo9
Relativity Space8
Relativity6
Zeta Global5
Xanadu5

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 Iceberg

NamePostingsShare
London224.6%
New York City183.7%
San Francisco183.7%
Pune163.3%
Long Beach142.9%
Bengaluru132.7%
Boston132.7%
San Jose132.7%
Toronto132.7%

Skills commonly paired with Iceberg

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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 Iceberg by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s Iceberg postings by all Iceberg 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 2,595 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
4730e5fc014fa9e5
data_as_of
2026-09-30
window_days
90
Hiring engineers who use Iceberg?

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