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

As of 2026-09-30, traces appears in 492 job postings indexed by Skillenai over the past 90 days — Software Engineer has the most postings mentioning traces, with demand share up 3.8% vs the prior 4 weeks.

Last updated · 90d ending 2026-09-30

Postings · last 90 days
492
Demand vs prior month
up 3.8% vs the prior 4 weeks
Top role · 22.6% of skill postings
Top hiring metro
San Francisco

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Frequently asked questions about traces

+Is traces in demand in 2026?

Yes. traces appears in 492 job postings indexed by Skillenai over the 90 days ending 2026-09-30. Software Engineer accounts for the most postings mentioning traces (22.6% of all postings mentioning traces).

+What jobs require traces?

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 traces are Developer Experience Engineer (9.5% of that role’s postings mention traces), Site Reliability Engineering Manager (7.8% of that role’s postings mention traces), CloudOps Engineer (6.2% of that role’s postings mention traces).

+What skills are commonly paired with traces?

Across job postings indexed by Skillenai (90 days ending 2026-09-30), traces most often appears alongside metrics, logs, observability, Kubernetes, Python.

+Where is traces most in demand?

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

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

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

+Which skills come before and after traces?

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 traces — last 90 days

Salary distribution

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

Career paths around traces

Skills documented before and after this skill across employer changes.

Historical career profiles · all locations

Skills before traces

Before tracespython → traces: 2 observed employer moves with this skill pairdata profiling → traces: 1 observed employer moves with this skill pairData factories → traces: 1 observed employer moves with this skill pairAzure DevOps → traces: 1 observed employer moves with this skill pairQualtrics → traces: 1 observed employer moves with this skill pairPostgreSQL → traces: 1 observed employer moves with this skill pairPower BI → traces: 1 observed employer moves with this skill pairAzure Databricks → traces: 1 observed employer moves with this skill pairtracespython: 2 movespython2 movesdata profiling: 1 movesdata profiling1 movesData factories: 1 movesData factories1 movesAzure DevOps: 1 movesAzure DevOps1 movesQualtrics: 1 movesQualtrics1 movesPostgreSQL: 1 movesPostgreSQL1 movesPower BI: 1 movesPower BI1 movesAzure Databricks: 1 movesAzure Databricks1 moves

Skills after traces

No published outgoing skill pairs yet.

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: python2
Before: data profiling1
Before: Data factories1
Before: Azure DevOps1
Before: Qualtrics1
Before: PostgreSQL1
Before: Power BI1
Before: Azure Databricks1

Roles most likely to require traces

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

RolePostings mentioning skill% of role postings mentioning skill
Developer Experience Engineer29.5%
Site Reliability Engineering Manager47.8%
CloudOps Engineer26.2%
QA Manager14.5%
DevOps Consultant14.3%
Systems Integration Engineer13.6%
Observability Engineer13.4%
Site Reliability Engineer673.1%
Product Architect13.1%
Software Development Engineer in Test (SDET)42.8%

Roles with the most traces postings

RolePostings mentioning skillShare of skill postings
Software Engineer11122.6%
Site Reliability Engineer6713.6%
Backend Engineer5912.0%
DevOps Engineer204.1%
AI Engineer173.5%
Engineering Manager163.3%
Platform Engineer163.3%
Product Manager132.6%
Cloud Engineer61.2%
Forward Deployed Engineer61.2%

Top companies posting jobs requiring traces

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

Top companies posting jobs requiring traces
CompanyPostings · 90 days
Grafana Labs44
Grafanalabs13
Cisco13
Nebius11
Elastic8
CLERA7
Tekion7
Grab6
Mastercard5
Wayve5

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 traces

NamePostingsShare
San Francisco244.9%
New York City193.9%
Bengaluru153.0%
London122.4%
Sunnyvale102.0%
Dublin81.6%
Seattle81.6%
Stockholm71.4%
Amsterdam61.2%

Skills commonly paired with traces

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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 traces by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s traces postings by all traces 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
438cc9da1c9c4652
data_as_of
2026-09-30
window_days
90
Hiring engineers who use traces?

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