Entity resolution jobs in 2026 — demand, top roles hiring, and related skills
As of 2026-10-30, Entity resolution appears in 329 job postings indexed by Skillenai over the past 90 days — Data Engineer has the most postings mentioning Entity resolution, with demand share up 25.3% vs the prior 4 weeks.
Last updated · 90d ending 2026-10-30
Which roles want Entity resolution?
Upload your resume and Skillenai will show which roles your Entity resolution experience fits, which skills you already cover, and what is missing.
Frequently asked questions about Entity resolution
+Is Entity resolution in demand in 2026?
Yes. Entity resolution appears in 329 job postings indexed by Skillenai over the 90 days ending 2026-10-30. Data Engineer accounts for the most postings mentioning Entity resolution (14.3% of all postings mentioning Entity resolution).
+What jobs require Entity resolution?
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 Entity resolution are Data Platform Architect (6.5% of that role’s postings mention Entity resolution), AI Technical Lead (3.7% of that role’s postings mention Entity resolution), Data Governance Manager (3.7% of that role’s postings mention Entity resolution).
+What skills are commonly paired with Entity resolution?
Across job postings indexed by Skillenai (90 days ending 2026-10-30), Entity resolution most often appears alongside Python, SQL, machine learning, knowledge graphs, data modeling.
+Where is Entity resolution most in demand?
As of 2026-10-30, the metro areas posting the most jobs requiring Entity resolution are New York City, San Francisco, London, Hyderabad, Berlin, according to the Skillenai jobs index.
+How can I keep up with new Entity resolution content and jobs?
Skillenai indexes news, blog posts, and research papers mentioning Entity resolution alongside the jobs index. You can subscribe to a daily email digest of new Entity resolution content from your Skillenai account.
+Which skills come before and after Entity resolution?
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 Entity resolution — last 90 days
Salary distribution
Box = 25th–75th percentile · tick = median · whisker = 10th–90th · USD, annualized
Career paths around Entity resolution
Skills documented before and after this skill across employer changes.
Historical career profiles · all locations
Skills before Entity resolution
Skills after Entity resolution
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: NLP | 2 |
| Before: ETL | 1 |
| Before: Android project analysis | 1 |
| Before: on-premise Hadoop cluster | 1 |
| Before: reliability | 1 |
| Before: Hive/bline | 1 |
| Before: Salesforce | 1 |
| Before: cloud-based | 1 |
| After: GenAI | 1 |
| After: RDF | 1 |
| After: ETL | 1 |
| After: Named Entity Recognition | 1 |
| After: graph data science | 1 |
| After: zero-shot learning | 1 |
| After: tensorflow | 1 |
| After: OWL | 1 |
Roles most likely to require Entity resolution
Among roles with at least 20 postings in the same period.
| Role | Postings mentioning skill | % of role postings mentioning skill |
|---|---|---|
| Data Platform Architect | 2 | 6.5% |
| AI Technical Lead | 1 | 3.7% |
| Data Governance Manager | 1 | 3.7% |
| Applied Data Scientist | 1 | 3.6% |
| Lead Data Scientist | 3 | 3.5% |
| Senior Data Engineer | 1 | 3.4% |
| AI Data Engineer | 2 | 3.0% |
| Data Science Engineer | 1 | 2.9% |
| Engineering Product Manager | 1 | 2.9% |
| Data Engineering Lead | 1 | 1.9% |
Roles with the most Entity resolution postings
| Role | Postings mentioning skill | Share of skill postings |
|---|---|---|
| Data Engineer | 47 | 14.3% |
| Software Engineer | 38 | 11.6% |
| Data Scientist | 37 | 11.2% |
| Product Manager | 31 | 9.4% |
| AI Engineer | 14 | 4.3% |
| Forward Deployed Engineer | 14 | 4.3% |
| Data Analyst | 10 | 3.0% |
| Engineering Manager | 9 | 2.7% |
| Full Stack Engineer | 8 | 2.4% |
| Machine Learning Engineer | 8 | 2.4% |
Top companies posting jobs requiring Entity resolution
Employers ranked by indexed job postings in the last 90 days.
| Company | Postings · 90 days |
|---|---|
| CLERA | 23 |
| Wise | 9 |
| Guidehouse | 7 |
| ZoomInfo | 7 |
| ServiceNow | 7 |
| Kalepa | 6 |
| Baselayer | 4 |
| Mapbox | 4 |
| 4 | |
| Mastercard | 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 Entity resolution
| Name | Postings | Share |
|---|---|---|
| New York City | 23 | 7.0% |
| San Francisco | 22 | 6.7% |
| London | 13 | 4.0% |
| Hyderabad | 8 | 2.4% |
| Berlin | 7 | 2.1% |
| Bengaluru | 6 | 1.8% |
| Mountain View | 5 | 1.5% |
| Arlington | 4 | 1.2% |
| Barcelona | 4 | 1.2% |
Skills commonly paired with Entity resolution
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 Entity resolution by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s Entity resolution postings by all Entity resolution 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
- aa772e9301f7cff1
- data_as_of
- 2026-10-30
- window_days
- 90