Q: Tell us about your technical experience?

Structure: (1) Current—responsibilities, stack, scale. (2) Achievements—quantified. (3) Prior—progression. (4) Depth—systems, design choices. Example: 'Senior DE, 6 yrs; own streaming platform, 5B events/day, Kafka+Flink; cut costs 40% via optimization; prior batch ETL Spark+Airflow; Python, SQL, AWS/GCP.' Tailor to JD.

Q: What is the difference between SAFE_CAST() and CAST()?

CAST: Error on failure (e.g., 'abc'→INT). SAFE_CAST: NULL on failure. Use SAFE_CAST for dirty data; CAST when failure should propagate. Example: SAFE_CAST(col AS DATE) in ETL. Handle NULLs downstream.

Question 1

Have you worked on Data Warehousing projects?

Accepted Answer

**Architectural context**: A data warehouse is the semantic layer between raw data and business decisions. Design choices—star vs snowflake, SCD strategy, partitioning—directly impact query latency, storage cost, and maintenance burden. **Key responsibilities**: (1) **Schema design**: Star for BI simplicity, snowflake for normalized flexibility. SCD Type 2 for slowly changing dimensions (audit trail, point-in-time correctness)....

Question 2

What is the difference between OLTP and OLAP?

Accepted Answer

**Why the distinction exists**: They serve different access patterns. OLTP = many small, random writes and point reads. OLAP = few, large sequential scans and aggregations. Optimizing for one degrades the other. **OLTP**: Row-oriented storage (fast single-row access). Normalized schema (3NF) to avoid update anomalies. Indexes for lookup (B-tree). ACID for consistency. High concurrency via locking/mvcc. Examples: PostgreSQL, MySQL, Oracle....

Question 3

What is the difference between SQL and NoSQL databases?

Accepted Answer

**Why both exist**: SQL excels at structured data, complex joins, and strong consistency. NoSQL excels at unstructured/semi-structured data, horizontal scale, and flexible schema. **SQL (relational)**: Fixed schema, ACID, vertical scale (or managed horizontal via Citus, etc.). Optimized for joins and aggregations. Best for: transactional systems, reporting, anything requiring referential integrity. **NoSQL**: Schema-flexible, BASE (eventual consistency), horizontal scale....

Question 4

Calculate the total sales amount for customers born between 1998-01-15 and 2000-01-15.

Accepted Answer

**SQL**: SELECT SUM(s.amount) AS total_sales FROM sales s JOIN customers c ON s.customer_id = c.id WHERE c.birth_date BETWEEN '1998-01-15' AND '2000-01-15'. **Note**: BETWEEN inclusive. **Spark**: sales.join(customers, 'customer_id').filter((col('birth_date') >= '1998-01-15') & (col('birth_date') <= '2000-01-15')).agg(F.sum('amount'))....

Question 5

Identify the top 5 customers with the highest purchases in the last quarter.

Accepted Answer

Use window/ranking with clear assumptions. SQL (BigQuery/Snowflake): WITH quarterly AS (SELECT customer_id, SUM(amount) total FROM transactions WHERE transaction_date >= DATE_SUB(CURRENT_DATE(), INTERVAL 3 MONTH) GROUP BY customer_id), ranked AS (SELECT customer_id, total, RANK() OVER (ORDER BY total DESC) rk FROM quarterly) SELECT customer_id, total, rk FROM ranked WHERE rk <= 5....

Question 6

Tell us about your technical experience?

Accepted Answer

Structure: (1) Current—responsibilities, stack, scale. (2) Achievements—quantified. (3) Prior—progression. (4) Depth—systems, design choices. Example: 'Senior DE, 6 yrs; own streaming platform, 5B events/day, Kafka+Flink; cut costs 40% via optimization; prior batch ETL Spark+Airflow; Python, SQL, AWS/GCP.' Tailor to JD.

Question 7

What is the difference between SAFE_CAST() and CAST()?

Accepted Answer

CAST: Error on failure (e.g., 'abc'→INT). SAFE_CAST: NULL on failure. Use SAFE_CAST for dirty data; CAST when failure should propagate. Example: SAFE_CAST(col AS DATE) in ETL. Handle NULLs downstream.

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Aarete General Interview Questions

Companies asking these questions

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More Interview Prep Guides

Get All Answers in PDF Format