Ingram Micro Data Engineer 1 Interview Questions and Answers

Q1. Tableau Questions 1. Difference between dimensions and measures. 2. What is RLS? 3. What are the functions you can assign in RLS? 4. Explain what is drill down approach. 5. What is LOD? 6. What is a calcul...read more
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Q2. SQL Questions 1. In employee table find the 2nd highest salary. 2. Find the highest average salary in department 3. Given two tables(sales & product) find total sales per category 4. Two questions to find ...read more
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Q1. Self introduction
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Maths grammar & communication

Q1. Typeing speed skills check same use paragraph
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Q2. Typing speed 10 minutes
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Q1. Move on next round easy
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Q1. What are joins and its type
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Q2. Tell me about Dax query
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Q1. How to handle imbalanced data
Ans. 
Handling imbalanced data involves techniques like resampling, using different algorithms, and adjusting class weights.
• Use resampling techniques like oversampling or undersampling to balance the data

• Utilize algorithms that are robust to imbalanced data, such as Random Forest or XGBoost

• Adjust class weights in the model to give more importance to minority class
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Q2. Write python code to get correlation between two features
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Python code to calculate correlation between two features
• Import pandas library

• Use df.corr() method to calculate correlation between two features

• Specify the two features as arguments to the corr() method
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Q3. How to handle outliers
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Outliers can be handled by removing, transforming, or imputing them based on the context of the data.
• Identify outliers using statistical methods like Z-score, IQR, or visualization techniques.

• Remove outliers if they are due to data entry errors or measurement errors.

• Transform skewed data using log transformation or winsorization to reduce the impact of outliers.

• Impute outliers with the median or mean if they are valid ...read more
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Q1. How will you handle client when task is not completed on time.
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I would communicate openly with the client, provide updates on the progress, and discuss potential solutions to meet the deadline.
• Communicate proactively with the client about the delay

• Provide regular updates on the progress of the task

• Discuss potential solutions to meet the deadline, such as reallocating resources or extending the timeline

• Apologize for the delay and take responsibility for the situation

• Ensure that the...read more
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Q2. ML,DL AND NLP questions
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It was pair programming round where we need to attempt a couple of Spark Scenario along with the Interviewer. You will have a boiler plate code with some functionalities to be filled up. You will be assessed on writing clean and extensible code and test cases.

Q1. Questions will be based on the Project where they try to assess the depth of understading you have on your project, data quality checks, handling failure scenarios, reasoning behind choice of tech stack
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Q1. Types of clusters in Databricks
Ans. 
Types of clusters in Databricks include Standard, High Concurrency, and Single Node clusters.
• Standard clusters are used for general-purpose workloads

• High Concurrency clusters are optimized for concurrent workloads

• Single Node clusters are used for development and testing purposes
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Q2. What is catalyst optimiser in Spark
Ans. 
Catalyst optimizer is a query optimizer in Apache Spark that leverages advanced techniques to optimize and improve the performance of Spark SQL queries.
• Catalyst optimizer uses a rule-based and cost-based optimization approach to generate an optimized query plan.

• It performs various optimizations such as constant folding, predicate pushdown, and projection pruning to improve query performance.

• Catalyst optimizer also leve...read more
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Q3. What is explode function
Ans. 
Explode function is used in Apache Spark to split an array into multiple rows.
• Used in Apache Spark to split an array into multiple rows

• Creates a new row for each element in the array

• Commonly used in data processing and transformation tasks
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Q4. Delta lake vs data lake
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Delta Lake is an open-source storage layer that brings ACID transactions to Apache Spark and big data workloads.
• Delta Lake provides ACID transactions, schema enforcement, and time travel capabilities on top of data lakes.

• Data lakes are a storage repository that holds a vast amount of raw data in its native format until it is needed.

• Delta Lake is optimized for big data workloads and provides reliability and performance ...read more
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Q5. What is RDD ?
Ans. 
RDD stands for Resilient Distributed Dataset, a fundamental data structure in Apache Spark.
• RDD is a fault-tolerant collection of elements that can be operated on in parallel.

• RDDs are immutable, meaning they cannot be changed once created.

• RDDs support two types of operations: transformations (creating a new RDD from an existing one) and actions (returning a value to the driver program).
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Q1. Write a few python queries and some live sql coding and pyspark coding
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Q2. Machine learning questions. Way too deep. which is not even required
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Q1. Sql regarding question was there
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