Data Engineer mock test
EasyEnv, Remote, World Wide, 6 questions
Sign in to applyAbout the role
A data engineer builds and runs the pipelines and storage that turn raw data from applications and outside sources into tables that analysts, products and models can trust. The work is part software engineering and part operations: correct data, delivered on time, at a cost the business can carry.
Most teams work in SQL and Python, orchestrate jobs with Airflow or a similar tool, transform data with dbt or Spark, and keep it in a warehouse or lakehouse such as Snowflake, BigQuery or Databricks.
What you will do
- Design, build and maintain batch and streaming pipelines, from ingestion to modelled tables.
- Model data for analysis: facts, dimensions, keys, and how history is kept.
- Make pipelines safe to rerun and backfill, so that a retry never duplicates or loses records.
- Handle late and out-of-order data, and decide how and when results are corrected.
- Find and fix slow queries and expensive reports, and protect production databases from analytical load.
- Monitor data quality and freshness, debug production data issues, and write the runbooks.
What we look for
- Expert SQL: reading query plans, indexing, and rewriting queries that are slow or run too often.
- Production Python, plus experience with an orchestrator such as Airflow, Dagster or Prefect.
- Experience with a relational database and a cloud data warehouse or lakehouse.
- Understanding of idempotency, incremental loads, and the trade-offs between batch and streaming.
- Git, the command line, and testing and deploying data code like any other code.
Nice to have
- dbt in production, Spark or PySpark, and Kafka or another streaming platform.
- Data quality tooling such as Great Expectations or Elementary.
- Infrastructure as code and CI/CD for data platforms.
About this mock test
One hour on a real Linux machine, in a terminal in your browser. You fix a database query storm and a slow report, then answer short written questions on safe pipeline reruns, batch and streaming, data modelling and late data.
This is practice. There is no job at the end of it. It is the same interview format employers run on EasyEnv, so you can measure yourself against what companies hiring for this role ask for, and see where you need more work.
Applying needs a free EasyEnv account, so the company knows who applied and you can follow your application. The interview runs on a real machine, so it needs a desktop browser.
