Software Engineer II
Microsoft Hyderabad, Telangana, India
Job Description
"Embark on a journey to become a Software Engineer II at Microsoft, where innovation meets collaboration, and limitless possibilities await."
As a Software Engineer II at Microsoft, you will be part of the Azure Data engineering team, leading the transformation of analytics in the world of data. With a wide range of products like databases, data integration, big data analytics, messaging & real-time analytics, and business intelligence, our portfolio includes industry-leading solutions such as Microsoft Fabric, Azure SQL DB, Azure Cosmos DB, Azure PostgreSQL, Azure Data Factory, Azure Synapse Analytics, Azure Service Bus, Azure Event Grid, and Power BI.
Our mission is to build the data platform for the age of AI, powering a new class of data-first applications. As a Software Engineer II, you will play a critical role in shaping the future of data engineering, collaborating with cross-functional teams, and driving innovation to meet the evolving needs of our customers.
Why you should learn this:
The demand for skilled software engineers is high, with a projected growth rate of 21% from 2020 to 2030, much faster than the average for all occupations.
Expected Salary: According to Glassdoor, the average salary for a Software Engineer II at Microsoft is around $141,000 - $250,000 per year, depending on location and experience.
How it works:
- Step 1: Develop a strong foundation in software engineering principles, including data structures, algorithms, and software design patterns.
- Step 2: Gain hands-on experience with Azure Data engineering tools and technologies, including Azure SQL DB, Azure Cosmos DB, Azure Data Factory, and Azure Synapse Analytics.
Core Concepts to Master
Azure Data Engineering Fundamentals
Understand the core concepts of Azure Data engineering, including data integration, big data analytics, messaging & real-time analytics, and business intelligence. Learn about the key features and capabilities of Azure Data Factory, Azure Synapse Analytics, and Azure Service Bus.
Cloud-Native Architecture
Learn about cloud-native architecture patterns and design principles, including microservices, event-driven architecture, and serverless computing. Understand how to design and implement cloud-native applications using Azure services such as Azure Functions and Azure Storage.
Data Science and Machine Learning
Gain an understanding of data science and machine learning concepts, including data preprocessing, feature engineering, and model training. Learn about Azure services such as Azure Machine Learning and Azure Databricks, which can be used to build and deploy machine learning models.
Interview Questions (Beginner)
- What is Azure Data engineering, and how does it relate to data science and machine learning?
- Can you explain the difference between Azure Data Factory and Azure Synapse Analytics?
- How do you design and implement data pipelines using Azure Data Factory?
Job Overview
Advance Questions
- • Can you describe a scenario where you would use Azure Functions to implement a serverless architecture?
- • How do you optimize the performance of a data warehouse using Azure Synapse Analytics?
- • Can you explain the concept of data governance in Azure Data engineering, and how it relates to data security and compliance?