What questions are asked in McKinsey Data Engineer interviews?

Recent candidates report role-specific technical depth, system design or case prompts, and behavioral STAR questions. "Explain OAuth2 / OIDC flow for a B2B SaaS integration…" is among frequently reported topics.

Is domain-specific tech mandatory for McKinsey Data Engineer?

Strong fundamentals are required; stack depth signals vary by team. Panels often probe production scenarios even when the JD lists it as preferred.

How many rounds are there in McKinsey Data Engineer interviews?

Most loops include 3–5 rounds: recruiter screen, technical depth, system or domain panel, and behavioral/hiring-manager. Timelines often run 3–6 weeks.

How difficult is the McKinsey Data Engineer interview?

Difficulty is Medium–High. Candidates who practice real questions with AI mocks and follow-up chains outperform passive reading.

What SQL and data topics are asked at McKinsey?

Data-heavy tracks report warehousing, ETL, optimization, and modeling questions. Match prep to your specialization and recent candidate reports.

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Interview question

Explain OAuth2 / OIDC flow for a B2B SaaS integration

Asked in McKinsey Data Engineer interviews

Asked by

49% candidates

Difficulty

Medium

Round

Technical Round

AI synthesized from candidate reports

Back to Questions

Question 2 of 4

Explain OAuth2 / OIDC flow for a B2B SaaS integration

Medium59% Candidate ReportsTECHNICALMcKinseyData Engineer

Question

Explain OAuth2 / OIDC flow for a B2B SaaS integration

High-Level Approach

Authorization code with PKCE; short-lived access; secure refresh storage.