How do I approach Data Manipulation (SQL/Python) interview questions?

Data Manipulation (SQL/Python) questions require understanding of core concepts and practice. PracHub provides solutions with explanations to help you master data manipulation (sql/python) interviews.

What difficulty level is this interview question?

This is a Medium difficulty Data Manipulation (SQL/Python) question, commonly asked during Technical Screen rounds at EY.

What role is this question designed for?

This question is commonly asked for Data Scientist candidates at EY during technical interviews.

Design a data platform enablement

Last updated: Mar 29, 2026

Quick Overview

This question evaluates a candidate's competence in designing a compliant cloud data platform, covering architecture (ingestion, storage, governance, transformation, consumption), data contracts and lineage, operational considerations like SLAs/SLOs, partitioning, backfill/late-arrival handling, cost guardrails, and phased rollout planning.

Oct 13, 2025, 9:49 PM

Data Scientist

Technical Screen

Data Manipulation (SQL/Python)

Design a pragmatic data‑platform enablement for a mid‑tier retail bank migrating to cloud under PII and data‑residency constraints. Describe the target architecture (ingestion, storage, governance, transformation, consumption), data contracts, lineage, and access patterns. Specify SLAs/SLOs, partitioning strategy, backfill/late‑arrival handling, cost guardrails, and a 3‑wave rollout plan with success metrics. Include the one thing you would deliberately postpone and why.

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