How our test assesses Elasticsearch skills
In Neuroworx's Elasticsearch test, candidates will need to answer a range of questions targeting an intermediate level of knowledge using the platform. This includes using features such as indexing and searching, aggregation, scaling Elasticsearch clusters, adding and removing nodes, and API integration - in addition to this, candidates are assessed on terminology, using the interface and general best practices.
The test is designed to indicate how well a candidate understands Elasticsearch based on a final test score, which can then be compared to the scores of other applicants.
The multiple-choice questions consist of one correct answer and two to four distractors. The distractors are generic mistakes or misconceptions, which makes the test challenging and helps measure a candidate's proficiency more accurately.
During the development process, the test was rigorously analysed to maximise reliability and validity in line with industry best practices. It was created and tested by Elasticsearch specialists and psychometric experts, and field-tested with a representative sample of job applicants who have varying Elasticsearch experience, just like you might find in a talent pool.
Each test is reviewed by a panel of individuals representing diverse backgrounds to check for any sensitivity, fairness, face validity and accessibility issues. This ensures each candidate has a fair chance of demonstrating their true level of Elasticsearch proficiency and feels the test is high quality.
Our software tests are monitored to ensure they are up-to-date and optimised for performance.