SOFTWARE SKILLS

Elasticsearch test for hiring

See how candidates reason through Elasticsearch configuration, mappings, queries, and ingest tasks.

10 minutes
15 questions
Intermediate
Multiple choice
Questions in English
Phone and desktop

Use this test free See the question formats

The short answer

The Elasticsearch test is an intermediate, 10-minute hiring assessment with 15 multiple-choice questions. Candidates interpret configuration files, mappings, search requests, ingest pipelines, and sample documents. It measures hands-on knowledge of cluster setup, indexing, search queries, and data connections for software engineers, data engineers, analysts, and others who run or build on Elasticsearch.

What it measures

Hands-on knowledge of configuring Elasticsearch clusters, mapping and indexing data, writing search queries, and connecting common data tools.

Cluster setup and configuration

Candidates interpret Elasticsearch configuration and choose an appropriate cluster setup.

Mappings and index design

Questions ask candidates to read mappings and make choices about index design and data indexing.

Search queries and APIs

Candidates assess search requests, query language behavior, and REST API results.

Ingest and integration

Questions cover bringing data in with Logstash, Beats, and ingest pipelines, then viewing it in Kibana.

Question formats

Multiple choice

The candidate: Reads a short situation, table or statement and picks the right answer, or every right answer.

You see: Whether the candidate knows the material well enough to apply it, not just recognize it.

15 questions in 10 minutes, served one at a time.

Roles this test fits

Software engineers, data engineers, data analysts, search and logging engineers, platform and site reliability engineers, and administrators who run or build on Elasticsearch.

What the Elasticsearch test can show

Look beyond resume claims
Candidates work through configuration files, mappings, search requests, pipelines, and sample documents, giving you specific evidence to review.
See applied reasoning
Questions ask what a request returns or which setup fits, helping you explore how candidates use Elasticsearch in practical situations.
Focus follow-up time
Use results to identify areas for a work sample or interview, such as cluster configuration, index design, or data integration.
Check connected tools
The test covers data coming in through Logstash, Beats, and ingest pipelines, as well as viewing it in Kibana.

What you get for each candidate

Example report (fictional data)Elasticsearch

79%Percentile 64. Benchmark: HireValid candidates, n = 2,292

Cluster setup and configuration82%

Mappings and index design85%

Search queries and APIs84%

Ingest and integration63%

Integrity ScoreHigh confidence

Stayed on the test tab throughout
No pasted answers
Answered at a steady pace

Scores, profiles and integrity signals are evidence for you to review alongside an interview, never an automatic decision.

Use this test free

Test setup and review signals

Each candidate receives a different set of questions from large question pools. Questions appear in a different order for each attempt, and answer options are shuffled. The browser shows one question at a time, and answer keys stay on HireValid’s servers. The 10-minute timer runs on the server; reloading brings back the same question with only the remaining time. Candidates cannot go back to an earlier question. Copying or selecting question text is blocked, and a blocked copy attempt is recorded. HireValid records signals such as time away from the test tab, pastes into answers, and answers faster than a question can be read. An Integrity Score and evidence timeline summarize signals for employer review; neither decides on its own. Webcam photos can be added at random moments with the candidate’s consent.

How we prevent AI cheating · Integrity signals

Use the score as evidence

Review the score alongside a short work sample and a structured interview; do not use it alone or as a hiring verdict. Ask the candidate to work through a search request or explain a mapping choice from a role-relevant example. For adjacent skills, consider the PostgreSQL, SQL Coding: Querying, or Docker tests when they match the role.

Structured interview questions

How would you decide whether a sample document needs a different mapping before indexing?
Listen for a reasoned link between the data, the mapping, and the index design, rather than a definition.
What would you check to understand why a search request returns unexpected documents?
Look for a step-by-step approach that refers to the request, the sample documents, and the result.
How would you choose a way to bring a given set of records into Elasticsearch?
Listen for a practical choice involving Logstash, Beats, or an ingest pipeline and how the data would be viewed in Kibana.

Understand scoring and benchmarks

Fairness and accommodations

Questions follow current Elasticsearch 8 behavior and say so when a detail differs between versions. Each question shows the configuration, request or sample data it asks about, so nothing depends on remembering exact error text or menu layouts. Sample data uses neutral subjects such as orders, sensors, logs and products, with no money symbols, names from many backgrounds, and no knowledge beyond the job.

You can give any candidate extra time as an accommodation. Results are evidence for a person to review, never an automatic decision.

Provisional: reliability is reported once 200 candidates have completed it.

Read our fairness approach

Test details

Short, practical questions on running and using Elasticsearch at an intermediate level. Candidates read configuration files, index mappings, search requests, ingest pipelines and small sets of sample documents, then say what happens, what a request returns, or which setup is right. The questions cover cluster configuration, mappings and index design, the query language and REST APIs, and getting data in with Logstash, Beats and ingest pipelines, then viewing it in Kibana.

Questions are in English.
No aids are needed.
Each question is answered once, in order, with no going back.
4 practice questions, 4 minutes, before the timed test.

Elasticsearch, Kibana, Logstash, Beats, Filebeat, Apache Kafka are trademarks of their owners. HireValid is not affiliated with or endorsed by them.

Frequently asked questions

What does the Elasticsearch test measure?+

It measures hands-on knowledge of cluster configuration, mappings and index design, search queries and REST APIs, and data connections. Candidates interpret files, requests, pipelines, and sample documents, rather than simply reciting terminology.

How long is the Elasticsearch test, and what is its format?+

The assessment has 15 multiple-choice questions and takes 10 minutes. Candidates cannot return to earlier questions. A separate practice set has four questions and takes four minutes.

Which roles can use the Elasticsearch test?+

It is intended for intermediate roles such as software engineers, data engineers, data analysts, search and logging engineers, platform and site reliability engineers, and administrators who run or build on Elasticsearch.

How should I use an Elasticsearch test score in hiring?+

Treat the score as evidence for a person to review, then explore relevant areas with a work sample and structured interview. For example, ask candidates to reason through a search request, mapping, or data-ingest choice. Do not let the score decide on its own.