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

As of 2026-11-05, data mapping appears in 830 job postings indexed by Skillenai over the past 90 days — Business Analyst has the most postings mentioning data mapping, with demand share down 0.5% vs the prior 4 weeks.

Last updated · 90d ending 2026-11-05

Postings · last 90 days
830
Demand vs prior month
down 0.5% vs the prior 4 weeks
Top role · 18.0% of skill postings
Top hiring metro
Bengaluru

Which roles want data mapping?

Upload your resume and Skillenai will show which roles your data mapping experience fits, which skills you already cover, and what is missing.

Frequently asked questions about data mapping

+Is data mapping in demand in 2026?

Yes. data mapping appears in 830 job postings indexed by Skillenai over the 90 days ending 2026-11-05. Business Analyst accounts for the most postings mentioning data mapping (18.0% of all postings mentioning data mapping).

+What jobs require data mapping?

According to the Skillenai jobs index over the 90 days ending 2026-11-05, among roles with at least 20 postings, the highest shares mentioning data mapping are Data Governance Analyst (9.1% of that role’s postings mention data mapping), Technical Business Analyst (8.5% of that role’s postings mention data mapping), Business Systems Analyst (8.3% of that role’s postings mention data mapping).

+What skills are commonly paired with data mapping?

Across job postings indexed by Skillenai (90 days ending 2026-11-05), data mapping most often appears alongside SQL, Python, ETL, Agile, data governance.

+Where is data mapping most in demand?

As of 2026-11-05, the metro areas posting the most jobs requiring data mapping are Bengaluru, New York City, San Francisco, Pune, Toronto, according to the Skillenai jobs index.

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

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

+Which skills come before and after data mapping?

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 mapping — last 90 days

Salary distribution

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

Career paths around data mapping

Skills documented before and after this skill across employer changes.

Historical career profiles · all locations

Skills before data mapping

Before data mappingsql → data mapping: 18 observed employer moves with this skill pairTableau → data mapping: 8 observed employer moves with this skill pairpython → data mapping: 7 observed employer moves with this skill pairdata analysis → data mapping: 6 observed employer moves with this skill pairETL → data mapping: 5 observed employer moves with this skill pairPower BI → data mapping: 5 observed employer moves with this skill pairgap analysis → data mapping: 5 observed employer moves with this skill pairUse Cases → data mapping: 5 observed employer moves with this skill pairdata mappingsql: 18 movessql18 movesTableau: 8 movesTableau8 movespython: 7 movespython7 movesdata analysis: 6 movesdata analysis6 movesETL: 5 movesETL5 movesPower BI: 5 movesPower BI5 movesgap analysis: 5 movesgap analysis5 movesUse Cases: 5 movesUse Cases5 moves

Skills after data mapping

After data mappingdata mapping → ETL: 9 observed employer moves with this skill pairdata mapping → sql: 9 observed employer moves with this skill pairdata mapping → Excel: 6 observed employer moves with this skill pairdata mapping → python: 6 observed employer moves with this skill pairdata mapping → stored procedures: 5 observed employer moves with this skill pairdata mapping → gap analysis: 4 observed employer moves with this skill pairdata mapping → Azure DevOps: 4 observed employer moves with this skill pairdata mapping → kubernetes: 4 observed employer moves with this skill pairdata mappingETL: 9 movesETL9 movessql: 9 movessql9 movesExcel: 6 movesExcel6 movespython: 6 movespython6 movesstored procedures: 5 movesstored procedures5 movesgap analysis: 4 movesgap analysis4 movesAzure DevOps: 4 movesAzure DevOps4 moveskubernetes: 4 moveskubernetes4 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: sql18
Before: Tableau8
Before: python7
Before: data analysis6
Before: ETL5
Before: Power BI5
Before: gap analysis5
Before: Use Cases5
After: ETL9
After: sql9
After: Excel6
After: python6
After: stored procedures5
After: gap analysis4
After: Azure DevOps4
After: kubernetes4

Roles most likely to require data mapping

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

RolePostings mentioning skill% of role postings mentioning skill
Data Governance Analyst29.1%
Technical Business Analyst118.5%
Business Systems Analyst68.3%
Finance Data Analyst27.4%
Integration Engineer117.1%
Fullstack Software Engineer66.9%
Data Governance Manager26.7%
Systems Analyst36.2%
Integrations Engineer26.1%
Integration Architect65.5%

Roles with the most data mapping postings

RolePostings mentioning skillShare of skill postings
Business Analyst14918.0%
Data Analyst546.5%
Data Engineer475.7%
Product Manager384.6%
Software Engineer354.2%
Solutions Architect222.7%
Solution Architect161.9%
Product Owner151.8%
Data Architect141.7%
Technical Product Manager141.7%

Top companies posting jobs requiring data mapping

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

Top companies posting jobs requiring data mapping
CompanyPostings · 90 days
Kyndryl14
Clara13
State Street12
INSPYR Solutions9
ING9
Veeva Systems9
Manulife9
Twilio8
Broadridge8
Capco8

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 mapping

NamePostingsShare
Bengaluru222.7%
New York City222.7%
San Francisco151.8%
Pune111.3%
Toronto101.2%
Charlotte70.8%
Manila70.8%
Austin60.7%
Boston60.7%

Skills commonly paired with data mapping

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 2026-11-05. 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 mapping by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s data mapping postings by all data mapping 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: 0.3% to 0.3%. 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 2,472 identified employers and covers 71% of earlier and 70% of latest indexed postings. Windows: 2026-07-07 to 2026-10-05 and 2026-08-04 to 2026-11-02 (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
b4e8799f364d8765
data_as_of
2026-11-05
window_days
90
Compiled by Jared Rand · Data sourced from the Skillenai labor market index