Software Engineer II
Microsoft Bengaluru, Karnataka, India
Job Description
"Unlock the power of innovation at Microsoft's Azure Data engineering team as a Software Engineer II, where you'll collaborate with passionate innovators to transform the world of data analytics."
As a Software Engineer II at Microsoft's Azure Data engineering team, you'll play a key role in shaping the future of data analytics by designing, developing, and deploying cutting-edge data engineering solutions. With a focus on building a data platform for the age of AI, you'll work with a talented team of engineers to power a new class of data-first applications.
In this role, you'll have the opportunity to work on a wide range of exciting projects, from building scalable data pipelines to developing real-time analytics solutions. You'll collaborate with cross-functional teams to drive innovation and deliver high-quality results, all while staying up-to-date with the latest advancements in data engineering and AI.
Why you should learn this:
With the increasing adoption of cloud-enabled technologies, the demand for skilled data engineers is skyrocketing. According to industry reports, the global data engineering market is expected to grow by 20% annually, making it an exciting and in-demand field to pursue.
Expected Salary: As a Software Engineer II at Microsoft, you can expect a competitive salary ranging from $180,000 to $250,000 per year, depending on your experience and qualifications.
How it works:
- Step 1: Learn the fundamentals of data engineering, including data modeling, data warehousing, and data transformation.
- Step 2: Gain hands-on experience with popular data engineering tools and technologies, such as Azure Data Factory, Azure Synapse Analytics, and Power BI.
Core Concepts to Master
Data Engineering Principles
Understand the key principles of data engineering, including data quality, data governance, and data security. Learn how to design and implement scalable data pipelines, data warehouses, and data lakes.
Cloud-Native Data Engineering
Learn how to design and build cloud-native data engineering solutions using Azure services, such as Azure Data Factory, Azure Synapse Analytics, and Power BI. Understand how to leverage serverless computing, containerization, and microservices architecture to build scalable and secure data engineering solutions.
Real-Time Analytics and Event-Driven Architecture
Understand how to build real-time analytics solutions using event-driven architecture and streaming data technologies, such as Apache Kafka, Apache Flink, and Azure Event Grid. Learn how to design and implement scalable and fault-tolerant event-driven systems.
Interview Questions (Beginner)
- What is data engineering, and how does it differ from data science?
- Can you explain the concept of data warehousing and data lakes?
- How do you ensure data quality and data governance in a data engineering project?
Job Overview
Advance Questions
- • Can you describe a scenario where you had to design and implement a scalable data pipeline using Azure Data Factory?
- • How do you approach data modeling and data transformation in a data engineering project?
- • Can you explain the concept of serverless computing and how it applies to data engineering?