ITC Infotech Lead Engineer Interview Questions, Process, and Tips for Experienced

Python libraries commonly used by data engineers include Pandas, NumPy, Matplotlib, and Scikit-learn.

• Pandas: Used for data manipulation and analysis.

• NumPy: Provides support for large, multi-dimensional arrays and matrices.

• Matplotlib: Used for creating visualizations and plots.

• Scikit-learn: Offers machine learning algorithms and tools for data analysis.

PySpark is a Python API for Apache Spark, a powerful open-source distributed computing system.

• PySpark allows users to write Spark applications using Python programming language.

• It provides high-level APIs in Python for Spark's functionality, making it easier to work with large datasets.

• PySpark can be used for data processing, machine learning, graph processing, and more.

• Example: PySpark can be used to perform data anal...read more

Delta Lake is an open-source storage layer that brings ACID transactions to Apache Spark and big data workloads.

• Provides ACID transactions for big data workloads

• Ensures data reliability and quality by enabling schema enforcement and data versioning

• Supports batch and streaming data processing

• Improves data quality and reliability by enabling schema enforcement and data versioning

Create end to end pipelines in Data Factory with SQL and ASQL as source and target respectively.

• Use Copy Data activity to move data from SQL source to ASQL target

• Define linked services for SQL and ASQL in Data Factory

• Create datasets for SQL and ASQL tables

• Map columns between source and target datasets

• Configure data flow activities for any transformations needed