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Apache Spark for Data Engineers test for hiring

See how candidates reason through Spark code, job execution, transformations, performance, and streaming.

10 menit
15 pertanyaan
Intermediate
Multiple choice
Questions in Inggris
Phone and desktop

Use this test free See the question formats

Jawaban singkat

The Apache Spark for Data Engineers test is a 10-minute, intermediate hiring assessment for data engineers, big data engineers, analytics engineers, and platform engineers. Its 15 multiple-choice questions use short PySpark or Scala code to assess job execution, DataFrame transformations, Spark Core and tuning, and streaming.

Hal yang diukur

Working knowledge of Apache Spark: how jobs run, DataFrame transformations, Spark Core and tuning, and streaming.

Spark fundamentals and execution

Checks how Spark jobs run and what short code examples do or return.

Data transformation

Covers how candidates reason about DataFrame transformations in Spark.

Spark Core and performance

Checks Spark Core knowledge and how to make processing faster or more dependable.

Streaming and graph processing

Covers reasoning about streaming and graph-processing work alongside batch processing.

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

Data engineers, big data engineers, analytics engineers and platform engineers who build or maintain Spark pipelines, at a mid level.

What this test can show

Reading code, not reciting terms
Most questions show a few lines of PySpark or Scala and ask what the job does, what it returns or how Spark runs it, so candidates have to trace real code.
No marks lost to version defaults
Every setting an answer depends on is stated in the question, so the result reflects reasoning about Spark rather than memory of one release's defaults.
Batch and streaming in one result
Streaming and graph processing sit beside batch execution and tuning, which helps when the role maintains both kinds of Spark pipeline.

What you get for each candidate

Example report (fictional data)Apache Spark for Data Engineers

67%Percentile 37. Benchmark: HireValid candidates, n = 539

Spark fundamentals and execution55%

Data transformation72%

Spark Core and performance69%

Streaming and graph processing70%

Integrity ScoreTingkat keyakinan tinggi

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 controls and review signals

Each candidate receives a different question set, with questions and answer options shuffled. The browser shows one question at a time, and answer keys stay on HireValid’s servers. Timing runs on the server; reloading restores the same question with only the remaining time. Text cannot be copied or selected, and blocked copy attempts are recorded. Personal invitation links expire, and a finished test cannot be taken again. HireValid summarizes signals such as time away from the test tab, pastes, and unusually fast answers in an Integrity Score with an evidence timeline for employer review. It does not decide on its own. With candidate consent, employers can add webcam photos at random moments.

Cara kami mencegah kecurangan dengan AI · Integrity signals

Use the result as evidence

Review the score alongside a work sample based on Spark pipeline work and a structured interview. Treat it as evidence to discuss, not a decision by itself. If the role also calls for adjacent skills, consider the PySpark test, Data Extraction, Transformation, and Loading (ETL) test, or Snowflake test.

Pertanyaan wawancara terstruktur

Walk me through how you would investigate a Spark job that returns fewer rows than expected.
Listen for a clear approach to tracing the job and examining its transformations and output.
How would you decide which part of a Spark pipeline to examine when a run is slow?
Listen for a reasoned way to investigate performance and explain the next step.
How would you check a streaming pipeline after changing a transformation?
Listen for how the candidate would review the change and assess the resulting processing.

Understand scoring and benchmarks

Fairness and accommodations

Questions use neutral data such as sensor readings, page views, orders and shipments, with no money symbols, idioms or local knowledge, and names from many backgrounds. Code is short and written in common PySpark or Scala, with every setting the answer depends on stated in the question, so candidates are not marked down for not knowing one version's defaults. The reading level is kept plain so the test measures Spark skill rather than English.

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.

Baca pendekatan kami terhadap keadilan

Test details

A timed check of how well a data engineer uses Apache Spark to process large volumes of data. Short questions, most built around a few lines of PySpark or Scala code, ask what a job does, what it returns, how Spark runs it and how to make it faster or more dependable, across batch and streaming work.

Questions are in English.
No aids are needed.
Each question is answered once, in order, with no going back.
4 practice questions, 3 minutes, before the timed test.

Apache Spark, Python, Scala, Apache Parquet are trademarks of their owners. HireValid is not affiliated with or endorsed by them.

Pertanyaan yang sering diajukan

Who should take the Apache Spark for Data Engineers test?+

It is designed for mid-level data engineers, big data engineers, analytics engineers, and platform engineers who build or maintain Spark pipelines. Use it when the role calls for working knowledge of Spark execution, transformations, performance, or streaming.

How does the Apache Spark for Data Engineers test keep questions clear?+

Questions use neutral examples such as sensor readings, page views, orders, and shipments. Code is short, written in common PySpark or Scala, and states the settings needed to answer, so candidates are not expected to know version-specific defaults.

Can candidates try the Apache Spark for Data Engineers practice set?+

Yes. The practice set has 4 questions and takes 3 minutes, so candidates can see how short PySpark or Scala snippets appear on screen before the timed test starts. No aids are needed for the test itself.

What is the format and timing of the Apache Spark for Data Engineers test?+

It has 15 multiple-choice questions and a 10-minute limit. Candidates cannot go back to an earlier question. The test is not desktop-only, and its questions are in English.