Data engineering fundamentals
Evaluate data lifecycle concepts, source systems, file formats, batch and streaming fundamentals, and warehouse architecture.
Data Engineer pre-employment test
Hire dependable engineers with a Data Engineer Pre-Employment Test.
Evaluate backend fundamentals, APIs, databases, system design, security, performance, testing, debugging, and practical problem-solving before technical interviews.
Data engineering fundamentalsDatabases & SQLREST APIs & servicesBig data technologies & security
Skill signals
What this assessment helps you evaluate
Measure the backend capabilities needed to build reliable APIs, data layers, services, and scalable production systems.
Databases & SQL
Assess dimensional modelling, star and snowflake schemas, normalisation, fact tables, dimensions, keys, and slowly changing dimensions.
API development
Test extraction, transformation, loading, orchestration, scheduling, idempotency, retries, dependencies, and pipeline reliability.
Big data technologies
Review Hadoop, Spark, Hive, Kafka, Flink, distributed processing, partitioning, and big-data architecture trade-offs.
Security
Assess AWS, Azure and GCP data services, warehouses, data lakes, orchestration tools, and cloud-native integration patterns.
Performance
Measure data profiling, validation, lineage, metadata, observability, governance, privacy, compliance, and quality controls.
Testing
Evaluate advanced SQL, joins, subqueries, CTEs, window functions, aggregations, and analytical query design.
Debugging
Identify production issues through logs, traces, exceptions, and structured root-cause analysis.
Assessment flow
A practical structure for fair backend screening
Move candidates through a consistent, job-relevant process with automated scoring and decision-ready reports.
01
Invite candidates
Send the assessment by email or share a secure test link with applicants.
02
Run timed tasks
Candidates solve backend coding, API, SQL, debugging, and architecture questions.
03
Auto-evaluate
Score correctness, test cases, code quality, performance, and practical reasoning.
04
Review reports
Compare candidates using skill breakdowns, question analysis, and hiring recommendations.
Score breakdown
Backend capability profile
Use cases
Where this assessment fits best
Backend recruitment
Validate role readiness before investing time in live technical interviews.
Specialist engineering roles
Assess API, database, platform, microservices, and software architecture skills.
Campus and graduate hiring
Identify applicants with strong fundamentals and practical learning potential.
Backend hiring
Screen backend developers using evidence, not résumés alone.
Use structured tasks, automated evaluation, and clear reports to shortlist stronger engineering candidates faster.