Equal Experts Data Engineer Interview Questions and Answers

Q1. Explain the Previous project from the resume
Ans. 
Developed a real-time data processing system for analyzing customer behavior on an e-commerce platform.
• Designed and implemented data pipelines using Apache Kafka for streaming data ingestion.

• Utilized Apache Spark for data processing and analysis to generate insights for business decisions.

• Implemented machine learning models for customer segmentation and personalized recommendations.

• Collaborated with cross-functional te...read more
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Q2. SQL window function
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Q1. Python - find max from array without using built in function
Ans. 
Find max from array in Python without using built-in function.
• Iterate through the array and compare each element with a variable storing the current maximum value.

• If the element is greater than the current maximum, update the variable.

• Return the variable after iterating through the entire array.
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Q2. Spark cluster configuration
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Q3. Python split data interview question
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Full c concept MCQ with IQ and Computaional Thinking

Q1. Number system convertion in c
Ans. 
Number system conversion in C involves converting numbers between different bases, such as decimal to binary or hexadecimal.
• Use functions like itoa() to convert integers to strings in different bases

• Use strtol() to convert strings to integers in different bases

• Remember to specify the base when converting numbers
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Q2. Pointers, struct, Data Structure
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Q1. Decimal to Binary Convertion
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Q2. Hexa Decimal to Binary convertion
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Forecasting problem - Predict daily sku level sales

Q1. What is difference between bias and variance
Ans. 
Bias is error due to overly simplistic assumptions, variance is error due to overly complex models.
• Bias is the error introduced by approximating a real-world problem, leading to underfitting.

• Variance is the error introduced by modeling the noise in the training data, leading to overfitting.

• High bias can cause a model to miss relevant relationships between features and target variable.

• High variance can cause a model to ...read more
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Q2. Parametric vs non parametruc model
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Parametric models make strong assumptions about the form of the underlying data distribution, while non-parametric models do not.
• Parametric models have a fixed number of parameters, while non-parametric models have a flexible number of parameters.

• Parametric models are simpler and easier to interpret, while non-parametric models are more flexible and can capture complex patterns in data.

• Examples of parametric models inc...read more
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Q1. Core java , spring interview questions
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Q2. Spring, basic logical interview questions
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Q1. Mostly behaviour questions and check the communication skills
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Q2. Basic questions likes collections and project etc.
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Q1. OOP questions SQL Questions Programming structure
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Q1. SQL questions MVC and C# related questions
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Aptitude test, basic maths and LR

SQL and Visualisation related

Q1. Asked for details after qualifying in test
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Q1. Hooks, What is React, Basic JS Questions.
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Q1. Scenario based question based on project related.
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Q1. React and Python basic questions.
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