Innovaccer Data Engineer 2 Interview Questions and Answers

In GD I was provided with general topics not related to technical concepts

Q1. Questions related to Python and SQL
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Q1. Discussed about my Salary expectations
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It was well designed

Q1. Basic Questions about data warehousing
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Q2. Dbt Scenarios
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Q1. Cache vs persist
Ans. 
Cache is used for temporary storage of data in memory, while persist is used for saving data to disk for long-term storage.
• Cache is typically faster as it stores data in memory for quick access.

• Persist saves data to disk for durability and long-term storage.

• Cache is often used for temporary data that can be recomputed if lost, while persist is used for important data that needs to be retained.

• Examples: Using cache for ...read more
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Q2. Broadcast join and other optimization techniques
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Q1. Sql window function
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Q2. Spark architecture, dataframe vs rdd
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Q3. Python reverse sentence
Ans. 
Reverse a sentence using Python
• Split the sentence into words using split() method

• Reverse the list of words using list slicing

• Join the reversed list of words back into a sentence using join() method
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Q4. Join based on nulls in sql
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Q1. Probability related
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Q2. Stats related like IQR etc.
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Q1. Difference between entropy & information gain
Ans. 
Entropy measures randomness in data, while information gain measures the reduction in uncertainty after splitting data.
• Entropy is used in decision trees to measure impurity in a dataset before splitting it.

• Information gain is used in decision trees to measure the effectiveness of a split in reducing uncertainty.

• Entropy ranges from 0 (pure dataset) to 1 (completely impure dataset).

• Information gain is calculated as the d...read more
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Q2. LSTM & GRU, Which to use when ?
Ans. 
LSTM for longer sequences, GRU for faster training and less complex models.
• Use LSTM for tasks requiring long-term dependencies and memory retention.

• Use GRU for faster training and simpler models with fewer parameters.

• Consider using LSTM for tasks like language translation or speech recognition.

• Consider using GRU for tasks like sentiment analysis or text generation.
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Time Series data were given, we have to provide some insights

Q1. Tell me about your self?
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Q2. What technology & tools u know ? And basic questions regarding that topics ?
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Q1. Job culture and job responsibilities ?
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Q2. Some questions on an analytical tools like power BI ?
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Q1. About the project and technical aspect
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It contain both Aptitude and Coding about base models and Deep learning too

Q1. What different models technique ?
Ans. 
Different models techniques include linear regression, decision trees, random forests, support vector machines, and neural networks.
• Linear regression is used for predicting continuous values.

• Decision trees are used for classification and regression tasks.

• Random forests are an ensemble method based on decision trees.

• Support vector machines are used for classification tasks.

• Neural networks are used for complex pattern re
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Q2. What are performance metric where to use what?
Ans. 
Different performance metrics are used for different types of machine learning models to evaluate their effectiveness.
• For classification models, metrics like accuracy, precision, recall, F1 score, and ROC-AUC are commonly used.

• For regression models, metrics like mean squared error (MSE), mean absolute error (MAE), and R-squared are commonly used.

• For clustering models, metrics like silhouette score and Davies-Bouldin in...read more
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Q1. Explain about Project
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Q2. What are problems faced in that project?
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Highly interactive and technical

1 hr test with focus on math and analytical thinking