Intermediate~2h
Data Quality & Testing in Data Engineering CoreInterview Readiness Check
Categories of data quality (completeness, freshness, uniqueness, distribution, schema), test-driven pipelines with dbt tests and Great Expectations, anomaly detection, the data contract pattern..
data qualityfreshnesscompletenessuniquenessGreat Expectationsdbt testsdata contractanomaly detection
Learning path
Try a sample question
A dashboard shows total revenue of ₹0 for yesterday. The pipeline succeeded without errors. Which data quality dimension is most likely violated?
A.Schema validity
B.Freshness
C.Uniqueness
D.Completeness — expected rows are missing, likely from an upstream drop
Sign up free to take the full check and see the answer with an explanation.
What this module tests
- Conceptual understanding of data quality & testing fundamentals
- Trade-offs and design decisions in real system scenarios
- data quality and freshness — applied knowledge
- Interview-style reasoning and explanation quality
Free to start
Take the Data Quality & Testing check →
10 questions · Dimension scoring · AI coach feedback · Shareable result
Test your knowledge — free →No credit card · Takes 10–15 min
Frequently asked questions
- What does the Data Quality & Testing check test?
- The check covers categories of data quality (completeness, freshness, uniqueness, distribution, schema), test-driven pipelines with dbt tests and great expectations, anomaly detection, the data contract pattern.. Questions span beginner to advanced difficulty and test both conceptual understanding and practical trade-off reasoning.
- What keywords should I know for Data Quality & Testing?
- Key concepts include: data quality, freshness, completeness, uniqueness, Great Expectations, dbt tests, data contract, anomaly detection. These frequently appear in data engineering core interviews at product and infrastructure companies.
- How many questions are in the check?
- Each check has 10 questions — a mix of MCQ and short-answer. You get scored by dimension (e.g., scalability, consistency) so you know exactly where to focus.
- How long does it take to study Data Quality & Testing?
- Most engineers spend around 2 hours on this module. The check itself takes about 10–15 minutes. You can retake it up to 3 times per day.
- What prerequisite knowledge do I need before Data Quality & Testing?
- Data Quality & Testing builds on Batch ETL & Pipeline Design. Complete those first for the best results.
- Is data quality, freshness, completeness covered?
- Yes. The Data Quality & Testing module covers data quality, freshness, completeness among other key concepts. The check includes questions that reflect real data engineering core interview patterns.