A DataEngineering Portal

For teams Log in Start practising free

Deloitte

SQL and modeling breadth over Spark depth.

14 questions

SQL · 2Python · 4PySpark · 8

Status	Title	Technology	Topic	Acceptance	Difficulty
○	25.Parse fixed-width log lines	Python	Data modeling	19.0%	Easy
○	13.Second highest salary per department	SQL	Window functions	23.9%	Easy
○	15.Find duplicate invoices	SQL	Deduplication	53.8%	Easy
○	21.Validate JSON records against a schema	Python	Data modeling	100.0%	Easy
○	82.Median salary per department	PySpark	Aggregation	100.0%	Medium
○	83.Pivot revenue into a column per category	PySpark	Aggregation	—	Medium
○	86.Quarantine the records that will not parse	PySpark	JSON Handling	—	Medium
○	87.Split a tag list into rows	PySpark	Array Handling	100.0%	Easy
○	88.Standardise free-text cities	PySpark	Data quality	100.0%	Easy
○	89.Unpivot quarterly targets	PySpark	Aggregation	—	Medium
○	92.Carry the last sensor reading forward	PySpark	Window functions	—	Medium
○	94.Year-over-year revenue growth	PySpark	Window functions	—	Medium
○	97.Detect schema drift between two batches	Python	Data quality	—	Easy
○	99.Reconcile two sources	Python	Joins	—	Easy

Community-reported interview topics. Not official Deloitte questions and no affiliation is implied.