Technical interview guide

Data Modeling Standards

Organization-wide conventions for naming, structuring, and typing data so it's consistent across every pipeline and team.

Read: 32 min
Practice MCQs: 25
Interview QA: 25
Edition: v4
Editorial status: Reviewed
Relevant for: Data Architect

Scope: PostgreSQL 18, W3C DCAT 3 and CSVW, Apache Avro and Parquet specifications, OpenLineage, and UK Data Standards Authority guidance current 2026-08-31.

Interview QA

Treat each question like a live interview question: answer out loud first (structure, assumptions, tradeoffs), then open the model answer to spot gaps and rehearse a tighter follow-up.

Curated: 2026-10-05 · Written: 2026-10-05 · Reviewed: 2026-10-03

QA-1

Create organization-wide data naming standards.

QA-2

Model a sales fact table without double counting.

QA-3

Standardize timestamps across global systems.

QA-4

Choose keys for a multi-tenant customer model.

QA-5

Define nullability standards for shared data.

QA-6

Design a conformed customer dimension.

QA-7

Choose a slowly changing dimension strategy.

QA-8

Evolve an Avro event with a new field.

QA-9

Standardize money and currency fields.

QA-10

Govern reference codes shared by many systems.

QA-11

How do enterprise semantic layer standards reconcile differences between physical storage schemas and business domain definitions?

QA-12

Migrate a widely used column name.

QA-13

Prevent overlapping effective intervals.

QA-14

Standardize Boolean and lifecycle status fields.

QA-15

Model deleted data with retention obligations.

QA-16

Create data modeling standards for JSON columns.

QA-17

Handle a schema change that narrows numeric precision.

QA-18

Design lineage standards across batch and streaming jobs.

QA-19

Evaluate whether to mandate one enterprise data model.

QA-20

How do automated linters and CI/CD validation rules verify naming conventions and surrogate key standards in data models?

QA-21

Create a standards exception process.

QA-22

Measure adoption of data modeling standards.

QA-23

Test a data modeling standard before rollout.

QA-24

Review a tabular exchange contract.

QA-25