Senior Software Engineer
Microsoft Bengaluru, Karnataka, India
Job Description
"Unlock the full potential of your career as a Senior Software Engineer at Microsoft, where innovation meets limitless possibilities."
As a Senior Software Engineer at Microsoft's Azure Data engineering team, you will be at the forefront of transforming analytics in the world of data, leveraging cutting-edge technologies to power a new class of data-first applications. With a portfolio of products that includes Microsoft Fabric, Azure SQL DB, and Azure Cosmos DB, among others, you will have the opportunity to make a meaningful impact on the industry.
Join a community of passionate innovators who are shaping the future of data engineering, and take your career to the next level with unparalleled opportunities for growth, learning, and collaboration.
Why you should learn this:
High demand for skilled data engineers, with a projected growth rate of 30% in the next 5 years
Expected Salary: $150,000 - $250,000 per year, depending on experience and location
How it works:
- Develop expertise in designing and building scalable data platforms using Azure data services
- Collaborate with cross-functional teams to deliver high-quality products that meet customer needs
Core Concepts to Master
Cloud-Native Data Engineering
Design and build data pipelines that leverage Azure data services to deliver real-time insights and analytics
Data Platform Architecture
Develop expertise in designing and implementing scalable data platforms that meet the needs of modern data-driven applications
Azure Data Services
Master the use of Azure data services, including Azure SQL DB, Azure Cosmos DB, and Azure Data Factory
Data Engineering Best Practices
Learn industry best practices for designing, building, and operating scalable data platforms
Interview Questions (Beginner)
- What is your experience with cloud-native data engineering?
- How do you approach designing and building scalable data platforms?
- What do you know about Azure data services, and how have you used them in the past?
Job Overview
Advance Questions
- • Can you describe a complex data engineering problem you've solved in the past, and how you approached it?
- • How do you optimize data pipelines for performance, reliability, and scalability?
- • What are some common pitfalls to avoid when designing and building data platforms, and how do you prevent them?