Automated Data Quality Frameworks | Dataford Interview Questions

How do you design and implement automated data quality and testing frameworks using tools like Python or Great Expectations?

Implement validate_records(records, required_fields, unique_fields, numeric_ranges) as a lightweight Python quality framework. Return a deterministic report identifying missing fields, invalid numeric ranges, and duplicate unique-field values. The output must contain valid and row-level errors fields.

Constraints

0 <= len(records) <= 500
Each record is a dictionary with string keys
required_fields and unique_fields contain strings
Each numeric_ranges value is a two-element array [minimum, maximum]
Range boundaries are inclusive
Only nonempty values participate in uniqueness checks

Function Signature

def validate_records(records, required_fields, unique_fields, numeric_ranges):

Your question is Automated Data Quality Frameworks. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.

Problem

How do you design and implement automated data quality and testing frameworks using tools like Python or Great Expectations?

Constraints

0 <= len(records) <= 500
Each record is a dictionary with string keys
required_fields and unique_fields contain strings
Each numeric_ranges value is a two-element array [minimum, maximum]
Range boundaries are inclusive
Only nonempty values participate in uniqueness checks

Function Signature

def validate_records(records, required_fields, unique_fields, numeric_ranges):

Your question is Automated Data Quality Frameworks. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.