Software Engineer 2
Microsoft Hyderabad, Telangana, India
Job Description
"Join the innovative Azure Data engineering team at Microsoft and be part of a revolutionary transformation in the world of data."
As a Software Engineer 2 at Microsoft, you will play a crucial role in shaping the future of data analytics and engineering. With a focus on cloud-enabled innovation, we're pushing the boundaries of what's possible in the world of data.
Our team is responsible for building and maintaining a suite of products that empower businesses to make data-driven decisions, including Microsoft Fabric, Azure SQL DB, Azure Cosmos DB, and more.
Why you should learn this:
The demand for skilled data engineers is skyrocketing, with a projected growth rate of 30% by 2025, making this a highly sought-after career path.
Expected Salary: $150,000 - $250,000 per year, with opportunities for advancement and professional growth.
How it works:
- Design and develop scalable data pipelines and architectures using Azure Data Factory, Azure Synapse Analytics, and other tools.
- Collaborate with cross-functional teams to integrate data solutions with business applications and services.
Core Concepts to Master
Azure Data Factory (ADF)
Learn how to design, deploy, and manage scalable data integration pipelines using ADF, including data transformation, data movement, and data quality checks.
Azure Synapse Analytics (ASA)
Discover how to build and manage enterprise-scale data warehouses and big data analytics solutions using ASA, including data governance, security, and performance optimization.
Interview Questions (Beginner)
- What is Azure Data Factory, and how does it differ from other data integration tools?
- Can you explain the concept of data transformation and how it relates to data quality checks?
- How do you ensure data security and governance in a big data analytics solution?
Job Overview
Advance Questions
- • Design a data pipeline using Azure Data Factory that integrates data from multiple sources and destinations. Explain your design decisions and trade-offs.
- • Describe a scenario where you would use Azure Synapse Analytics for big data analytics, and explain the benefits and challenges of this approach.
- • How do you optimize data performance in a large-scale data warehouse, and what tools and techniques do you use to achieve this?