Sainsburys Data Engineer Interview Questions and Answers

I was hiring drive. First round was coding test with medium to advanced SQL, data modelling and python questions

Q1. Data model e commerce application
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Q2. Higest nth rank and lowest rank if no of employees less than 2
Ans. 
If number of employees is less than 2, highest and lowest rank will be the same.
• If there are less than 2 employees, both highest and lowest rank will be the same.

• For example, if there is only 1 employee, their rank will be 1 which is both the highest and lowest rank.
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Q3. Event session data modeling
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Q1. Sql-self join, non equi join, window funtion, consecutive seats, data modeling, stock market maximum profit sql question
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Q1. This was hiring manager round. Detailed discussions on project and previous experience
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Q1. Strength, weakness and why myntra
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Q1. How would you optimize joins
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Q2. What are different Join strategies
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Coding test comprises simple string problem on hackerrank

Q1. Project explanation,
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Q1. Explain projects, python string pattern code, sql query
Ans. 
The question asks the candidate to explain projects, python string pattern code, and SQL query.
• Discuss the projects you have worked on as a data engineer, highlighting your role and the technologies used.

• Explain how you have used Python string pattern code to manipulate and analyze data.

• Provide an example of a SQL query you have written to extract and analyze data from a database.

• Emphasize the impact and results of you...read more
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Q1. Data partitioning
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Q2. Data clustering
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Majorly the interviews revolve around the following skills :
1. Advanced SQL
2. PYTHON (DSA)

Majorly the interviews revolve around the following skills :
1. Advanced SQL
2. python (DSA)

Q1. Which techniques you would have used on a system you have worked in the past to be able to optimise it further. (Deep knowledge of the databases is required)
Ans. 
I would have used indexing, query optimization, and data partitioning to optimize the system.
• Implement indexing on frequently queried columns to improve search performance.

• Optimize queries by using proper joins, filters, and aggregations.

• Partition large tables to distribute data across multiple storage devices for faster access.

• Use materialized views to precompute and store aggregated data for quicker retrieval.
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Q2. Situational questions on the ETL tools used and advantages and disadvantages of both
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Q1. Describe a complex situation you were in at workplace and how did you handle it?
Ans. 
Handled a complex data migration project by breaking it down into smaller tasks and collaborating with team members.
• Identified key stakeholders and their requirements

• Developed a detailed project plan with timelines and milestones

• Assigned specific tasks to team members based on their strengths and expertise

• Regularly communicated progress updates and addressed any issues promptly
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Python SQL code and objectives will come

Q1. Pyspark hdfs SQL python
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Q1. Python pyspark SQL databricks aws
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