Exponentia.ai Data Engineer Interview Questions and Answers

MCQ SQL round coding easy questions

Q1. Resume based questions mostly on SQL, Python, Cloud basic to medium level
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Q1. It was both mangerial and technical round similar to round 1 but more deep
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It was through a link they share and you need to write and submit your code, no execution needed.

Q1. R1 was about 40 mins and was a bit tough. Asked more about ADF, ADB, SQL, SQL DW
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Q1. R2: Was the toughest, asked for 40 mins and more than 30 questions were asked, lucky enough to answer all of them.
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Q1. Some Managerial questions for 30mins, handling conflicts, leadership skills etc
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Q1. Asked why I want to join fractal, why looking for other offer, biggest achievement etc
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Q1. The HR representative will seek to understand your experience and its alignment with the role.
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Q2. Salary expectations, Offers in hand
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Q1. What are the key features and functionalities of Snowflake?
Ans. 
Snowflake is a cloud-based data warehousing platform known for its scalability, performance, and ease of use.
• Snowflake uses a unique architecture called multi-cluster, which separates storage and compute resources for better scalability and performance.

• It supports both structured and semi-structured data, allowing users to work with various data types.

• Snowflake offers features like automatic scaling, data sharing, and ...read more
Answered by AI
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Q2. The interviewer asked several complex SQL questions that utilized analytical functions.
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Q3. I was asked to write some syntax-level code for Jinja statements in dbt.
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Q1. The interviewer, who was part of the senior management, inquired about dbt, its features, and my experience with dbt thus far.
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Q2. The interviewer reviewed my resume and inquired about the challenges I encountered in my previous roles and the methods I used to resolve them.
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Q1. Salary negotiations, Bonus discussions
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I cannot recall the platform, but it featured a combination of Python and SQL questions, with the majority being focused on SQL.

Q1. SQL basics like Indexes, Clustering, Keys, Data warehousing concepts, Normalization and Denormalization etc..
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Q2. SQL coding questions
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Q1. SQL questions to solve using different types of joins
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Q2. Questions based on project and data quality checks
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Q1. Behavioral questions
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Q2. Culture fit
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