Blackrock Associate Data Engineer Interview Questions and Answers

Q1. Tell me About Yourself
Ans. 
I am a data analyst with a background in statistics and experience in analyzing large datasets.
• Background in statistics

• Experience in analyzing large datasets

• Proficient in data visualization tools like Tableau

• Strong problem-solving skills

• Excellent communication skills
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Q2. Project working and day to day activities I do
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Q3. Rate Yourself In SQL out of 5
Ans. 
I would rate myself a 4 out of 5 in SQL proficiency.
• Proficient in writing complex SQL queries

• Experienced in optimizing database performance

• Familiar with data manipulation and analysis functions

• Comfortable working with large datasets
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Q4. Sql 3 question based on windows function
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Q5. Very basic python 2 Question
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Q6. What You do on power bi in your work Explain with full details workflow
Ans. 
I use Power BI to analyze and visualize data for insights and decision-making in my work.
• Connect to data sources to import data

• Transform and clean data using Power Query Editor

• Create relationships between different data tables

• Design interactive reports and dashboards

• Use DAX formulas for calculations and measures

• Share reports with stakeholders and collaborate on insights
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Q1. All 3 sql Questions very simple Round but they didn't provide any Data tables just tell this and that so it may get confusing I slove 2 out of three but rejected on this Round questions Are intermidate
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Q1. Big data , Optimization , Python basic , SQL intermediate
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Q2. Find max and min number without sorting Joins related Big data handling Optimization question
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Q1. Schema , python , sql
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Q2. Case study sql and python based
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Sales data from a leading manufacturer

Q1. What is spark,explain its ecosystem
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Q2. What are transformations, and how many types of transformations exist?
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Q3. Explain about spark job process and its planning
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Q4. What are the concepts of coalesce and repartition in data processing?
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Q5. Explain about oom and driverhead memory
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Q6. What is data skewness
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Normal aptitude round

Q1. SQL 4 QUESTION 1 BASIC 3 INTERMIDATE
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Q2. DATA WAREHOUSE DETAILS ITS IMP THEY WORK ON THIS SO ASK ALL INFO ABOUT THIS
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Q1. Project related discussions
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Q2. Meduim level SQl and DSA
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Q1. This was data modelling round
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Q2. Design a uber data model
Ans. 
Uber data model design for efficient storage and retrieval of ride-related information.
• Create tables for users, drivers, rides, payments, and ratings

• Include attributes like user_id, driver_id, ride_id, payment_id, rating_id, timestamp, location, fare, etc.

• Establish relationships between tables using foreign keys

• Implement indexing for faster query performance
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Q1. Power BI Difference between ALL() and ALLSELECTED()
Ans. 
ALL() ignores all filters in the query context, while ALLSELECTED() ignores only filters on columns in the visual.
• ALL() removes all filters from the specified column or table.

• ALLSELECTED() removes filters from the specified column or table, but keeps filters on other columns in the visual.

• Example: ALL('Table') would remove all filters on the 'Table' in the query context.

• Example: ALLSELECTED('Column') would remove filte...read more
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Q2. Excel Difference between COUNT() and COUNTA()
Ans. 
COUNT() counts only numeric values, while COUNTA() counts all non-empty cells.
• COUNT() counts only cells with numerical values.

• COUNTA() counts all non-empty cells, including text and errors.

• Example: COUNT(A1:A5) will count only cells with numbers, while COUNTA(A1:A5) will count all non-empty cells.
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Q1. Resume based questions like explain the projects that you have done.
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Q2. Sample dataset questions
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Maxium sub string and reverse a string

Q1. Basics of power bi and sql
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Q2. What are joins and types of join
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Q3. How to add date table in power bi
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Q1. Sql scenario based question on joins
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Q2. Window function questions
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Q3. Performance tuning
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Q4. Power bi dax question
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