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

As of 2026-09-30, data quality checks appears in 467 job postings indexed by Skillenai over the past 90 days — Data Engineer has the most postings mentioning data quality checks, with demand share up 5.0% vs the prior 4 weeks.

Last updated · 90d ending 2026-09-30

Postings · last 90 days
467
Demand vs prior month
up 5.0% vs the prior 4 weeks
Top role · 31.5% of skill postings
Data Engineer
Top hiring metro
New York City

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Frequently asked questions about data quality checks

+Is data quality checks in demand in 2026?

Yes. data quality checks appears in 467 job postings indexed by Skillenai over the 90 days ending 2026-09-30. Data Engineer accounts for the most postings mentioning data quality checks (31.5% of all postings mentioning data quality checks).

+What jobs require data quality checks?

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 data quality checks are Senior Data Engineer (8.3% of that role’s postings mention data quality checks), Business Intelligence Engineer (7.9% of that role’s postings mention data quality checks), Risk Analyst (7.3% of that role’s postings mention data quality checks).

+What skills are commonly paired with data quality checks?

Across job postings indexed by Skillenai (90 days ending 2026-09-30), data quality checks most often appears alongside SQL, Python, data modeling, data validation, data pipelines.

+Where is data quality checks most in demand?

As of 2026-09-30, the metro areas posting the most jobs requiring data quality checks are New York City, Bengaluru, London, San Francisco, Hyderabad, according to the Skillenai jobs index.

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

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

+Which skills come before and after data quality checks?

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 checks — last 90 days

Salary distribution

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

Career paths around data quality checks

Skills documented before and after this skill across employer changes.

Historical career profiles · all locations

Skills before data quality checks

Before data quality checkssql → data quality checks: 17 observed employer moves with this skill pairpython → data quality checks: 16 observed employer moves with this skill pairTableau → data quality checks: 12 observed employer moves with this skill pairPower BI → data quality checks: 10 observed employer moves with this skill pairsnowflake → data quality checks: 7 observed employer moves with this skill pairPySpark → data quality checks: 6 observed employer moves with this skill pairKafka → data quality checks: 6 observed employer moves with this skill pairAzure Data Factory → data quality checks: 5 observed employer moves with this skill pairdata qualitycheckssql: 17 movessql17 movespython: 16 movespython16 movesTableau: 12 movesTableau12 movesPower BI: 10 movesPower BI10 movessnowflake: 7 movessnowflake7 movesPySpark: 6 movesPySpark6 movesKafka: 6 movesKafka6 movesAzure Data Factory: 5 movesAzure Data Factory5 moves

Skills after data quality checks

After data quality checksdata quality checks → Power BI: 15 observed employer moves with this skill pairdata quality checks → sql: 11 observed employer moves with this skill pairdata quality checks → Tableau: 10 observed employer moves with this skill pairdata quality checks → python: 7 observed employer moves with this skill pairdata quality checks → Apache Spark: 6 observed employer moves with this skill pairdata quality checks → AWS: 6 observed employer moves with this skill pairdata quality checks → ETL: 6 observed employer moves with this skill pairdata quality checks → databricks: 5 observed employer moves with this skill pairdata qualitychecksPower BI: 15 movesPower BI15 movessql: 11 movessql11 movesTableau: 10 movesTableau10 movespython: 7 movespython7 movesApache Spark: 6 movesApache Spark6 movesAWS: 6 movesAWS6 movesETL: 6 movesETL6 movesdatabricks: 5 movesdatabricks5 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: sql17
Before: python16
Before: Tableau12
Before: Power BI10
Before: snowflake7
Before: PySpark6
Before: Kafka6
Before: Azure Data Factory5
After: Power BI15
After: sql11
After: Tableau10
After: python7
After: Apache Spark6
After: AWS6
After: ETL6
After: databricks5

Roles most likely to require data quality checks

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

RolePostings mentioning skill% of role postings mentioning skill
Senior Data Engineer38.3%
Business Intelligence Engineer67.9%
Risk Analyst37.3%
Lead Data Engineer45.3%
Financial Data Analyst25.3%
Analytics Engineering Director15.0%
Master Data Analyst15.0%
Data & Analytics Engineer14.8%
Analytics Engineer324.4%
Data Analytics Director14.2%

Roles with the most data quality checks postings

RolePostings mentioning skillShare of skill postings
Data Engineer14731.5%
Data Analyst5110.9%
Analytics Engineer326.9%
Data Scientist183.9%
Software Engineer132.8%
Business Analyst81.7%
Business Intelligence Engineer61.3%
Data Platform Engineer61.3%
Machine Learning Engineer51.1%
Lead Data Engineer40.9%

Top companies posting jobs requiring data quality checks

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

Top companies posting jobs requiring data quality checks
CompanyPostings · 90 days
WPP11
Ebury7
Allianz6
Wayve6
Accenture Federal Services5
General Dynamics Information Technology5
Gallup4
Twilio4
Honehealth4
Stripe4

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 checks

NamePostingsShare
New York City153.2%
Bengaluru132.8%
London122.6%
San Francisco112.4%
Hyderabad91.9%
Singapore81.7%
Toronto81.7%
Barcelona71.5%
Chicago71.5%

Skills commonly paired with data quality checks

SQL (348)Python (264)data modeling (159)data validation (147)data pipelines (128)DBT (124)ETL (123)data governance (105)CI/CD (99)Snowflake (95)

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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 data quality checks 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 checks postings by all data quality checks 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
08008b89dbb10a47
data_as_of
2026-09-30
window_days
90
Hiring engineers who use data quality checks?

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