Question 1

Data Warehouse Design from scratch

Accepted Answer

**Section 1 — The Context (The 'Why')**
The primary challenge for this design in SQL is balancing scale, cost, and reliability. At scale, naive approaches fail: single points of failure cause cascades, schema evolution breaks consumers, and over-provisioning explodes cost. Failure modes include silent data loss from non-idempotent writes, cascading job failures from tight coupling, and operational burden from manual intervention....

Question 2

Finding nth Highest Salary within each department

Accepted Answer

SELECT * FROM (SELECT *, DENSE_RANK() OVER (PARTITION BY department ORDER BY salary DESC) AS rk FROM employees) t WHERE rk = N. **Parameterize**: Prepared statement or session variable. **Efficiency**: Single pass; no correlated subquery....

Question 3

Normalization & Slowly Changing Dimensions (SCD) Type 2

Accepted Answer

SCD Type 2: history by adding rows. New row for each change with effective/expiry dates. Columns: surrogate_key, natural_key, attributes, effective_date, end_date, is_current. On change: set end_date on current row, insert new row with effective_date=now, end_date=infinity. Query current: WHERE is_current=1. Use for: dimension history (customer, product). Requires careful ETL to maintain timeline. **Why it matters**: Design choices compound at scale—wrong approach can cause 100× overhead....

Question 4

Optimizing Spark Jobs when they take longer than expected

Accepted Answer

Spark job tuning: (1) Increase partitions if underutilized—spark.default.parallelism, repartition. (2) Cache repeated stages. (3) Broadcast small tables. (4) Fix skew—salting, AQE. (5) Avoid unnecessary shuffles. (6) Coalesce before writes. (7) Tune executor memory, cores. (8) Use dynamic allocation. (9) Check data skew—monitor task duration variance. (10) Optimize UDFs—use native functions when possible....

Question 5

SQL Query Design: employees with highest salaries within each department

Accepted Answer

**Section 1 — The Context (The 'Why')**
The primary challenge for this design in SQL is balancing scale, cost, and reliability. At scale, naive approaches fail: single points of failure cause cascades, schema evolution breaks consumers, and over-provisioning explodes cost. Failure modes include silent data loss from non-idempotent writes, cascading job failures from tight coupling, and operational burden from manual intervention....

Question 6

What inspires you to join Walmart?

Accepted Answer

**Situation**: Context of the challenge. **Task**: Your responsibility. **Action**: Specific steps, tools, collaboration. **Result**: Quantified outcome. Walmart's scale in retail and supply chain creates unique data engineering challenges: billions of transactions, real-time inventory, and omnichannel analytics. The opportunity to build systems that directly improve customer experience and operational efficiency is compelling....

Walmart SQL Interview Questions

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Walmart SQL Interview Questions

Companies asking these questions

All 6 Questions

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