Skillenai

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

As of 2026-11-05, Data integrity appears in 971 job postings indexed by Skillenai over the past 90 days — Data Analyst has the most postings mentioning Data integrity, with demand share down 18.7% vs the prior 4 weeks.

Last updated · 90d ending 2026-11-05

Postings · last 90 days
971
Demand vs prior month
down 18.7% vs the prior 4 weeks
Top role · 8.0% of skill postings
Data Analyst
Top hiring metro
New York City

Which roles want Data integrity?

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Frequently asked questions about Data integrity

+Is Data integrity in demand in 2026?

Yes. Data integrity appears in 971 job postings indexed by Skillenai over the 90 days ending 2026-11-05. Data Analyst accounts for the most postings mentioning Data integrity (8.0% of all postings mentioning Data integrity).

+What jobs require Data integrity?

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 integrity are Sales Operations Analyst (18.8% of that role’s postings mention Data integrity), Quality Assurance Officer (15.4% of that role’s postings mention Data integrity), Manufacturing Systems Engineer (14.0% of that role’s postings mention Data integrity).

+What skills are commonly paired with Data integrity?

Across job postings indexed by Skillenai (90 days ending 2026-11-05), Data integrity most often appears alongside SQL, Python, data governance, data quality, data visualization.

+Where is Data integrity most in demand?

As of 2026-11-05, the metro areas posting the most jobs requiring Data integrity are New York City, London, Hyderabad, Toronto, San Francisco, according to the Skillenai jobs index.

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

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

+Which skills come before and after Data integrity?

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 integrity — last 90 days

Salary distribution

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

Career paths around Data integrity

Skills documented before and after this skill across employer changes.

Historical career profiles · all locations

Skills before Data integrity

Before Data integritypython → Data integrity: 30 observed employer moves with this skill pairsql → Data integrity: 16 observed employer moves with this skill pairPower BI → Data integrity: 15 observed employer moves with this skill pairTableau → Data integrity: 15 observed employer moves with this skill pairExcel → Data integrity: 14 observed employer moves with this skill pairdata analysis → Data integrity: 13 observed employer moves with this skill pairSQL Server → Data integrity: 11 observed employer moves with this skill pairETL → Data integrity: 10 observed employer moves with this skill pairDataintegritypython: 30 movespython30 movessql: 16 movessql16 movesPower BI: 15 movesPower BI15 movesTableau: 15 movesTableau15 movesExcel: 14 movesExcel14 movesdata analysis: 13 movesdata analysis13 movesSQL Server: 11 movesSQL Server11 movesETL: 10 movesETL10 moves

Skills after Data integrity

After Data integrityData integrity → sql: 16 observed employer moves with this skill pairData integrity → Tableau: 13 observed employer moves with this skill pairData integrity → python: 13 observed employer moves with this skill pairData integrity → ETL: 12 observed employer moves with this skill pairData integrity → Excel: 11 observed employer moves with this skill pairData integrity → Power BI: 10 observed employer moves with this skill pairData integrity → data pipelines: 7 observed employer moves with this skill pairData integrity → SQL queries: 7 observed employer moves with this skill pairDataintegritysql: 16 movessql16 movesTableau: 13 movesTableau13 movespython: 13 movespython13 movesETL: 12 movesETL12 movesExcel: 11 movesExcel11 movesPower BI: 10 movesPower BI10 movesdata pipelines: 7 movesdata pipelines7 movesSQL queries: 7 movesSQL queries7 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: python30
Before: sql16
Before: Power BI15
Before: Tableau15
Before: Excel14
Before: data analysis13
Before: SQL Server11
Before: ETL10
After: sql16
After: Tableau13
After: python13
After: ETL12
After: Excel11
After: Power BI10
After: data pipelines7
After: SQL queries7

Roles most likely to require Data integrity

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

RolePostings mentioning skill% of role postings mentioning skill
Sales Operations Analyst1218.8%
Quality Assurance Officer415.4%
Manufacturing Systems Engineer614.0%
Actuary313.6%
Master Data Analyst313.6%
Business Intelligence Director413.3%
Business Intelligence Specialist412.5%
Clinical Data Scientist312.0%
Quality Assurance Director79.7%
People Analytics Manager29.1%

Roles with the most Data integrity postings

RolePostings mentioning skillShare of skill postings
Data Analyst788.0%
Software Engineer616.3%
Data Scientist394.0%
Data Engineer383.9%
Product Manager293.0%
Business Analyst262.7%
Quality Assurance Specialist232.4%
Automation Engineer141.4%
Quality Assurance Manager141.4%
Sales Operations Analyst121.2%

Top companies posting jobs requiring Data integrity

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

Top companies posting jobs requiring Data integrity
CompanyPostings · 90 days
Novartis30
MSD26
Wise23
Eli Lilly and Company15
JJ14
Xometry13
AbbVie11
Gsk9
Amgen8
Barclays7

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 integrity

NamePostingsShare
New York City313.2%
London242.5%
Hyderabad212.2%
Toronto192.0%
San Francisco181.9%
Austin90.9%
Durham90.9%
Singapore90.9%
Washington90.9%

Skills commonly paired with Data integrity

SQL (290)Python (205)data governance (184)data quality (167)data visualization (137)Power BI (131)Tableau (122)data modeling (119)Data analysis (119)data validation (112)

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 integrity by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s Data integrity postings by all Data integrity 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: 0.5% to 0.4%. 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
bf345cc2e5223e57
data_as_of
2026-11-05
window_days
90
Compiled by Jared Rand · Data sourced from the Skillenai labor market index