best practices jobs in 2026 — demand, top roles hiring, and related skills
As of 2026-10-29, best practices appears in 162 job postings indexed by Skillenai over the past 90 days — Software Engineer has the most postings mentioning best practices, with demand share down 17.5% vs the prior 4 weeks.
Last updated · 90d ending 2026-10-29
Which roles want best practices?
Upload your resume and Skillenai will show which roles your best practices experience fits, which skills you already cover, and what is missing.
Frequently asked questions about best practices
+Is best practices in demand in 2026?
Yes. best practices appears in 162 job postings indexed by Skillenai over the 90 days ending 2026-10-29. Software Engineer accounts for the most postings mentioning best practices (8.6% of all postings mentioning best practices).
+What jobs require best practices?
According to the Skillenai jobs index over the 90 days ending 2026-10-29, among roles with at least 20 postings, the highest shares mentioning best practices are Data Engineering Lead (5.8% of that role’s postings mention best practices), Applied AI Architect (5.6% of that role’s postings mention best practices), Customer Program Manager (4.0% of that role’s postings mention best practices).
+What skills are commonly paired with best practices?
Across job postings indexed by Skillenai (90 days ending 2026-10-29), best practices most often appears alongside reference architectures, machine learning, automation, Engineering standards, data science.
+Where is best practices most in demand?
As of 2026-10-29, the metro areas posting the most jobs requiring best practices are San Francisco, Bengaluru, London, Paris, Bellevue, according to the Skillenai jobs index.
+How can I keep up with new best practices content and jobs?
Skillenai indexes news, blog posts, and research papers mentioning best practices alongside the jobs index. You can subscribe to a daily email digest of new best practices content from your Skillenai account.
+Which skills come before and after best practices?
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 best practices — last 90 days
Career paths around best practices
Skills documented before and after this skill across employer changes.
Historical career profiles · all locations
Skills before best practices
Skills after best practices
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: testing | 4 |
| Before: sql | 4 |
| Before: SQL Server | 4 |
| Before: C# | 3 |
| Before: security protocols | 3 |
| Before: python | 3 |
| Before: Spring Boot | 3 |
| Before: Git | 3 |
| After: RESTful APIs | 4 |
| After: Tableau | 4 |
| After: Java | 4 |
| After: sql | 4 |
| After: C# | 3 |
| After: Node.js | 3 |
| After: Git | 3 |
| After: AWS | 3 |
Roles most likely to require best practices
Among roles with at least 20 postings in the same period.
| Role | Postings mentioning skill | % of role postings mentioning skill |
|---|---|---|
| Data Engineering Lead | 3 | 5.8% |
| Applied AI Architect | 4 | 5.6% |
| Customer Program Manager | 1 | 4.0% |
| Product Operations Manager | 1 | 4.0% |
| AI Solution Engineer | 1 | 3.2% |
| Chief Architect | 1 | 2.4% |
| SAP Solution Architect | 1 | 2.4% |
| Electrical Engineering Manager | 1 | 2.2% |
| Java Engineer | 1 | 2.2% |
| Software Security Engineer | 1 | 2.1% |
Roles with the most best practices postings
| Role | Postings mentioning skill | Share of skill postings |
|---|---|---|
| Software Engineer | 14 | 8.6% |
| Solutions Architect | 11 | 6.8% |
| Engineering Manager | 10 | 6.2% |
| Solution Architect | 6 | 3.7% |
| Applied AI Architect | 4 | 2.5% |
| Program Manager | 4 | 2.5% |
| Applied AI Engineering Manager | 3 | 1.9% |
| Cybersecurity Engineer | 3 | 1.9% |
| Data Engineering Lead | 3 | 1.9% |
| Machine Learning Engineer | 3 | 1.9% |
Top companies posting jobs requiring best practices
Employers ranked by indexed job postings in the last 90 days.
| Company | Postings · 90 days |
|---|---|
| Anthropic | 10 |
| OpenAI | 4 |
| OneTrust | 4 |
| GE Vernova | 4 |
| Thetradedesk | 3 |
| Toast | 3 |
| Barclays | 3 |
| 3 | |
| CaptivateIQ | 2 |
| Quicken Loans | 2 |
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 best practices
| Name | Postings | Share |
|---|---|---|
| San Francisco | 9 | 5.6% |
| Bengaluru | 7 | 4.3% |
| London | 5 | 3.1% |
| Paris | 4 | 2.5% |
| Bellevue | 3 | 1.9% |
| Dublin | 3 | 1.9% |
| Madrid | 3 | 1.9% |
| Munich | 3 | 1.9% |
| New York City | 3 | 1.9% |
Skills commonly paired with best practices
Explore related pages
- Data Engineering Lead
- Applied AI Architect
- Customer Program Manager
- Product Operations Manager
- AI Solution Engineer
- Chief Architect
- SAP Solution Architect
- Electrical Engineering Manager
- reference architectures
- machine learning
- automation
- Engineering standards
- data science
- enterprise architecture
- software engineering
- security
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 2026-10-29. 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 best practices by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s best practices postings by all best practices 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
- 1459637634923176
- data_as_of
- 2026-10-29
- window_days
- 90