data quality controls jobs in 2026 — demand, top roles hiring, and related skills
As of 2026-10-30, data quality controls appears in 180 job postings indexed by Skillenai over the past 90 days — Data Engineer has the most postings mentioning data quality controls, with demand share down 11.5% vs the prior 4 weeks.
Last updated · 90d ending 2026-10-30
Which roles want data quality controls?
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Frequently asked questions about data quality controls
+Is data quality controls in demand in 2026?
Yes. data quality controls appears in 180 job postings indexed by Skillenai over the 90 days ending 2026-10-30. Data Engineer accounts for the most postings mentioning data quality controls (21.1% of all postings mentioning data quality controls).
+What jobs require data quality controls?
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 data quality controls are Data Product Owner (15.4% of that role’s postings mention data quality controls), Platform Engineering Manager (5.0% of that role’s postings mention data quality controls), Quantitative Finance Analyst (4.2% of that role’s postings mention data quality controls).
+What skills are commonly paired with data quality controls?
Across job postings indexed by Skillenai (90 days ending 2026-10-30), data quality controls most often appears alongside SQL, data governance, Python, data lineage, data pipelines.
+Where is data quality controls most in demand?
As of 2026-10-30, the metro areas posting the most jobs requiring data quality controls are London, Toronto, Chicago, Hyderabad, Singapore, according to the Skillenai jobs index.
+How can I keep up with new data quality controls content and jobs?
Skillenai indexes news, blog posts, and research papers mentioning data quality controls alongside the jobs index. You can subscribe to a daily email digest of new data quality controls content from your Skillenai account.
+Which skills come before and after data quality controls?
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 quality controls — last 90 days
Career paths around data quality controls
Skills documented before and after this skill across employer changes.
Historical career profiles · all locations
Skills before data quality controls
Skills after data quality controls
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.
| Connection | Moves |
|---|---|
| Before: employee engagement | 1 |
| Before: VBA | 1 |
| Before: real-time notifications | 1 |
| Before: ETL pipelines | 1 |
| Before: ETL | 1 |
| Before: mentored work | 1 |
| Before: SPSS | 1 |
| Before: python | 1 |
| After: testing | 1 |
| After: python | 1 |
| After: Apache Kafka | 1 |
| After: preprocessing techniques | 1 |
| After: excel xlookup | 1 |
| After: Power BI | 1 |
| After: sql | 1 |
| After: ANCOVA | 1 |
Roles most likely to require data quality controls
Among roles with at least 20 postings in the same period.
| Role | Postings mentioning skill | % of role postings mentioning skill |
|---|---|---|
| Data Product Owner | 6 | 15.4% |
| Platform Engineering Manager | 2 | 5.0% |
| Quantitative Finance Analyst | 1 | 4.2% |
| Data Governance Manager | 1 | 3.7% |
| Data Platform Architect | 1 | 3.2% |
| Data Analytics Consultant | 1 | 3.0% |
| Systems Analyst | 1 | 2.6% |
| AI Automation Engineer | 2 | 2.4% |
| Business Systems Engineer | 1 | 2.3% |
| Business Data Analyst | 2 | 2.1% |
Roles with the most data quality controls postings
| Role | Postings mentioning skill | Share of skill postings |
|---|---|---|
| Data Engineer | 38 | 21.1% |
| Data Analyst | 12 | 6.7% |
| Business Analyst | 8 | 4.4% |
| Data Product Owner | 6 | 3.3% |
| Analytics Engineer | 5 | 2.8% |
| Data Architect | 5 | 2.8% |
| Software Engineer | 4 | 2.2% |
| Data Platform Engineer | 3 | 1.7% |
| Quantitative Software Engineer | 3 | 1.7% |
| AI Automation Engineer | 2 | 1.1% |
Top companies posting jobs requiring data quality controls
Employers ranked by indexed job postings in the last 90 days.
| Company | Postings · 90 days |
|---|---|
| Ghr | 8 |
| Barclays | 4 |
| Vanguard | 4 |
| CIBC | 4 |
| AbbVie | 4 |
| Allstate | 4 |
| Www.experis.com | 4 |
| Version 1 | 3 |
| Mastercard | 3 |
| OMERS | 3 |
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 quality controls
| Name | Postings | Share |
|---|---|---|
| London | 9 | 5.0% |
| Toronto | 8 | 4.4% |
| Chicago | 7 | 3.9% |
| Hyderabad | 5 | 2.8% |
| Singapore | 4 | 2.2% |
| Bengaluru | 3 | 1.7% |
| Charlotte | 3 | 1.7% |
| New York City | 3 | 1.7% |
| Pune | 3 | 1.7% |
Skills commonly paired with data quality controls
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 data quality controls 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 controls postings by all data quality controls 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: 0.1% to 0.1%. 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 2,482 identified employers and covers 71% of earlier and 70% of latest indexed postings. Windows: 2026-06-30 to 2026-09-28 and 2026-07-28 to 2026-10-26 (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
- e1a6a4631a64f1e4
- data_as_of
- 2026-10-30
- window_days
- 90