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

As of 2026-09-28, data quality appears in 3,914 job postings indexed by Skillenai over the past 90 days — Data Engineer has the most postings mentioning data quality, with demand down 50% vs the prior 4 weeks.

Last updated · 90d ending 2026-09-28

Postings · last 90 days
3,914
Demand vs prior month
down 50% vs the prior 4 weeks
Top role · 17.6% of skill postings
Top hiring metro
New York City

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Frequently asked questions about data quality

+Is data quality in demand in 2026?

Yes. data quality appears in 3,914 job postings indexed by Skillenai over the 90 days ending 2026-09-28, with demand down 50% vs the prior 4 weeks. Data Engineer accounts for the most postings mentioning data quality (17.6% of all postings mentioning data quality).

+What jobs require data quality?

According to the Skillenai jobs index over the 90 days ending 2026-09-28, among roles with at least 20 postings, the highest shares mentioning data quality are Data Product Owner (43.8% of that role’s postings mention data quality), Enterprise Data Architect (30.0% of that role’s postings mention data quality), Data Engineer Intern (28.6% of that role’s postings mention data quality).

+What skills are commonly paired with data quality?

Across job postings indexed by Skillenai (90 days ending 2026-09-28), data quality most often appears alongside SQL, data governance, Python, data modeling, data pipelines.

+Where is data quality most in demand?

As of 2026-09-28, the metro areas posting the most jobs requiring data quality are New York City, San Francisco, London, Toronto, Bengaluru, according to the Skillenai jobs index.

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

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

Weekly job postings requiring data quality — last 90 days

Salary distribution

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

Roles most likely to require data quality

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

RolePostings mentioning skill% of role postings mentioning skill
Data Product Owner1443.8%
Enterprise Data Architect630.0%
Data Engineer Intern828.6%
Data Product Manager2427.0%
AI Data Engineer1723.0%
Data Architect13122.5%
Analytics Engineering Manager521.7%
Data Engineering Director1521.1%
Data Engineering Manager4821.1%
Analytics Engineering Director420.0%

Roles with the most data quality postings

RolePostings mentioning skillShare of skill postings
Data Engineer68917.6%
Data Analyst3067.8%
Data Scientist1694.3%
Product Manager1654.2%
Data Architect1313.3%
Software Engineer1163.0%
Analytics Engineer1082.8%
Business Analyst822.1%
Data Engineering Manager481.2%
Business Intelligence Analyst421.1%

Top metros hiring for data quality

NamePostingsShare
New York City1273.2%
San Francisco1253.2%
London1203.1%
Toronto571.5%
Bengaluru541.4%
Chicago441.1%
Paris381.0%
Singapore381.0%
Berlin340.9%

Skills commonly paired with data quality

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How this was computed

Counts derive from the Skillenai jobs index over the 90 days ending 2026-09-28. 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 quality by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s data quality postings by all data quality 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).

source
Skillenai jobs index, deduplicated daily
entity_id
1e02129706ff5033
data_as_of
2026-09-28
window_days
90
Hiring engineers who use data quality?

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