Evaluate SQL, ETL pipelines, and data modeling expertise

Data Engineer Test

Our data engineer test assesses the complete range of data engineering skills: from advanced SQL and ETL pipeline design to big data technologies and data quality practices. Identify candidates who build reliable data infrastructure.

Move beyond basic SQL tests with practical challenges that reveal how candidates actually approach data modeling, pipeline architecture, and working with data at scale—the skills that matter for building data platforms.

Data engineer test interface showing SQL queries, ETL pipeline diagram, and data model schema

Comprehensive evaluation of data engineering competencies

Skills Assessed

Our data engineer assessment evaluates both technical implementation skills and architectural thinking that distinguishes exceptional data engineers.

SQL & Database Design
Evaluate advanced SQL skills including complex queries, window functions, CTEs, and schema optimization.
ETL/ELT Pipelines
Assess ability to design and implement data extraction, transformation, and loading processes.
Data Modeling
Test understanding of dimensional modeling, star schemas, data vault, and normalization strategies.
Python for Data
Evaluate Python proficiency with pandas, PySpark, and data processing libraries.
Big Data Technologies
Assess knowledge of Spark, Hadoop ecosystem, distributed computing, and cloud data platforms.
Data Quality & Testing
Test understanding of data validation, quality checks, and testing data pipelines.

Practical assessments for data engineering roles

Test Components

Our data engineer test combines multiple assessment types to thoroughly evaluate candidates' data skills, from complex SQL to pipeline architecture.

Big data, cloud platforms, and data quality

Advanced Topics

Beyond core skills, assess experience with distributed systems, cloud data platforms, and building production-grade data infrastructure.

Why companies use CodeSubmit for data engineering hiring

Benefits for Hiring Teams

Join companies that use practical assessments to build high-performing data teams that power analytics and ML initiatives.

Test Real Data Skills
Move beyond basic SQL to assess complex analytical queries and pipeline design.
Evaluate Pipeline Design
See how candidates approach ETL architecture, error handling, and scalability.
Assess Big Data Experience
Verify hands-on experience with Spark, cloud platforms, and distributed systems.

Simple process, comprehensive evaluation

How the Data Engineer Test Works
1

Select Challenge Type

Choose from SQL challenges, ETL pipeline design, or data modeling exercises. Customize for your tech stack (Snowflake, BigQuery, Redshift, Spark).

2

Invite Candidates

Send assessment invitations. Candidates get access to database environments, sample datasets, and pipeline tooling pre-configured.

3

Review Submissions

Review SQL queries, pipeline code, and data models. Get AI-assisted analysis of query performance and design decisions.

4

Conduct Live Sessions

Use CodePair for live sessions where you can see candidates debug data issues, optimize queries, and discuss architecture decisions.

4-step assessment workflow: select challenge, invite candidates, review submissions, conduct live sessions

Start assessing candidates with practical data challenges

Ready to Hire Better Data Engineers?

Get started in minutes with our data engineer test. Access our library of SQL challenges, ETL exercises, and data modeling assessments.

Build data teams that deliver reliable, scalable data infrastructure.

I like how the library challenges are structured around on-the-job skills. The experience for candidates is excellent. They work locally with the IDE and tools they are most comfortable with.

Kevin Sahin
Kevin Sahin
Co-Founder @ ScrapingBee
Kevin Sahin