Purpose

This assessment is designed for early professional candidates with 2–4 years of experience in the IT, Software & ITeS industry, specifically targeting the AI - Data Engineer role. Its main goal is to evaluate foundational and intermediate skills relevant to data engineering tasks and responsibilities.

Overview

The assessment comprises a series of questions designed to evaluate the knowledge and skills of early professionals in the AI - Data Engineer role. It covers key areas such as data integration, streaming data processing, and distributed computing frameworks. The test assesses understanding of NoSQL databases, data lake architecture, and the role of data warehouses in business intelligence. Core traits evaluated include analytical thinking, problem-solving, and technical proficiency in data engineering tools and concepts. The structure ensures a comprehensive evaluation of candidates' readiness to handle data engineering tasks in real-world scenarios.

• Industry: IT, Software & ITeS
• Level: Early Professional
• Tag: AI - Data Engineer
• Total Questions: 25

Skills

• Data Integration
• Streaming Data Processing
• NoSQL Databases
• Data Lake Architecture
• Distributed Databases
• Distributed Computing
• Data Cataloging
• Data Workflow Management
• Columnar Storage
• Data Serialization
• Business Intelligence
• SQL Operations
• Database Normalization
• Data Pipeline Management

Ideal Roles

• AI - Data Engineer
• Data Engineer
• Big Data Engineer
• ETL Developer
• Data Architect