Sigmoid Data Engineer 1 Interview Questions and Answers

Q1. Explain any ML model.
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Q2. Create Dataframe from two lists.
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They will ask aptitude, reasoning and other questions as an online test to know your problem solving skills.

They will give a topic where either we have to speak or write on that topic

Q1. Intro, questions related to python, guesstimate questions
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Q2. Behavorial questions and other hr questions included
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Q1. Explain the RAG pipeline?
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RAG pipeline is a data processing pipeline used in data science to categorize data into Red, Amber, and Green based on certain criteria.
• RAG stands for Red, Amber, Green which are used to categorize data based on certain criteria

• Red category typically represents data that needs immediate attention or action

• Amber category represents data that requires monitoring or further investigation

• Green category represents data that...read more
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Q2. Explain Confusion metrics
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Confusion metrics are used to evaluate the performance of a classification model by comparing predicted values with actual values.
• Confusion matrix is a table that describes the performance of a classification model.

• It consists of four different metrics: True Positive, True Negative, False Positive, and False Negative.

• These metrics are used to calculate other evaluation metrics like accuracy, precision, recall, and F1 s...read more
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Q1. What is RDD and how its different from DF and Datasets
Ans. 
RDD stands for Resilient Distributed Dataset and is the fundamental data structure of Apache Spark.
• RDD is a distributed collection of objects that can be operated on in parallel.

• DataFrames and Datasets are higher-level abstractions built on top of RDDs.

• RDDs are more low-level and offer more control over data processing compared to DataFrames and Datasets.
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Q2. What is Partitioning and how to use colease and repartition
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Partitioning is the process of dividing data into smaller chunks for better organization and processing in distributed systems.
• Partitioning helps in distributing data across multiple nodes for parallel processing.

• Coalesce is used to reduce the number of partitions without shuffling data, while repartition is used to increase the number of partitions by shuffling data.

• Example: coalesce(5) will merge partitions into 5 pa...read more
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Q1. What is Spark and explian its architecture
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Spark is a distributed computing framework that provides an interface for programming entire clusters with implicit data parallelism and fault tolerance.
• Spark has a master-slave architecture with a driver program that communicates with a cluster manager to distribute work across worker nodes.

• It uses Resilient Distributed Datasets (RDDs) for fault-tolerant distributed data processing.

• Spark supports various programming l...read more
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Q2. What is DAG? how a spark job works how the dag gets created
Ans. 
DAG stands for Directed Acyclic Graph. It is a finite directed graph with no cycles.
• DAG is a collection of nodes connected by edges where each edge goes from one node to another, but no cycles are allowed.

• In the context of Spark, a DAG represents the sequence of transformations that need to be applied to the input data to get the final output.

• When a Spark job is submitted, Spark creates a DAG of the transformations spe...read more
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DSA and ML, AI, Coding question

Q1. Case study which was easy
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Q1. In depth questions on ML
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1 hr exam it is easy to crack

Aptitude test was divided into 3 parts and was not a typical quant, logical question it was more of an application based questions

Q1. What do you understand about the company?
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Q1. Mostly behavioural and situation based questions.
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