Software Engineer
Barclays Pune Division, Maharashtra, India
Job Description
"Unlock the future of digital banking as a Software Engineer at Barclays, driving innovation and excellence with cutting-edge technology."
As a Software Engineer at Barclays, you'll be at the forefront of revolutionizing our digital landscape, crafting unparalleled customer experiences through seamless technology integration.
With a strong focus on innovation and excellence, you'll have the opportunity to work with the latest technologies and frameworks, pushing the boundaries of what's possible in digital banking.
Why you should learn this:
Driven by the increasing adoption of digital banking, the demand for skilled Software Engineers is high, with a projected growth rate of 21% by 2028.
Expected Salary: £60,000 - £100,000 per annum, depending on experience, with opportunities for bonuses and benefits
How it works:
- Develop a solid understanding of software engineering principles, including object-oriented design, event-driven architecture, and distributed systems.
- Gain hands-on experience with Java 11+/17+, Spring Boot, REST APIs, Microservices, SQL Server, and other relevant technologies.
Core Concepts to Master
Event-Driven Architecture (EDA)
A software design pattern that organizes systems around events, enabling loose coupling, scalability, and fault tolerance.
Distributed Systems
A system of interconnected nodes that work together to achieve a common goal, often using technologies like Apache Kafka and Microservices.
Object-Oriented Design (OOD)
A software design approach that organizes code into objects, promoting modularity, reusability, and maintainability.
Interview Questions (Beginner)
- What is object-oriented design, and how do you apply it in software development?
- Can you explain the basics of event-driven architecture and its benefits?
- How do you handle errors and exceptions in distributed systems?
Job Overview
Advance Questions
- • Design a microservices architecture for a complex system, including APIs, databases, and messaging systems.
- • Implement a high-performance data processing pipeline using Apache Kafka and Spark.
- • Develop a scalable and fault-tolerant system using cloud-native technologies like AWS Lambda and DynamoDB.