Software Engineering
Microsoft Bengaluru, Karnataka, India
Job Description
"Join the Azure Data engineering team at Microsoft and be part of a world of limitless innovation, where passionate innovators come together to transform analytics in the world of data."
As a software engineer at Microsoft, you'll be at the forefront of developing cutting-edge data engineering solutions that power a new class of data-first applications.
With a wide range of products under our portfolio, including Microsoft Fabric, Azure SQL DB, Azure Cosmos DB, and more, you'll have the opportunity to work on diverse projects and contribute to the mission of building the data platform for the age of AI.
Why you should learn this:
The demand for skilled software engineers in data engineering is high, with a growing need for professionals who can design and develop scalable data solutions.
Expected Salary: $141,000 - $350,000 per year, depending on experience and location.
How it works:
- Step 1: Learn the fundamentals of software engineering, including data structures, algorithms, and software design patterns.
- Step 2: Gain experience with Azure Data engineering tools and services, such as Azure SQL DB, Azure Cosmos DB, and Azure Data Factory.
Core Concepts to Master
Data Engineering Fundamentals
Understanding data engineering principles, including data ingestion, processing, storage, and visualization. Learn about data modeling, data warehousing, and data governance.
Azure Data Engineering Services
Get hands-on experience with Azure Data engineering services, including Azure SQL DB, Azure Cosmos DB, Azure Data Factory, and Azure Synapse Analytics. Learn about data integration, data transformation, and data quality.
Cloud-Enabled Data Platforms
Learn about the design and development of cloud-enabled data platforms, including data lakes, data warehouses, and data hubs. Understand how to leverage cloud-based services for data processing, storage, and analytics.
Interview Questions (Beginner)
- What is data engineering, and why is it important?
- What are the key differences between a data warehouse and a data lake?
- How do you design a data pipeline for data ingestion and processing?
Job Overview
Advance Questions
- • Design a data architecture for a cloud-enabled data platform, including data ingestion, processing, storage, and visualization.
- • Explain the benefits and trade-offs of using Azure Data Factory for data integration and transformation.
- • How do you optimize data performance and scalability in a cloud-enabled data platform?