Software Engineer

Moneyview; Bengaluru; On-site; INR 1,800,000 - 2,800,000; Full time

Job summary

Moneyview is seeking a seasoned backend engineer in Bengaluru to design and implement scalable Java-based microservices using Spring/Spring Boot. You will create robust APIs, mentor teammates, and contribute to secure, well-tested code with a focus on reliability.

Applicants should have strong OO design, data structures expertise, and experience with relational databases, messaging systems, and big data tooling. Knowledge of AWS services is preferred.

Qualifications

• Strong Java backend experience with Spring/Spring Boot and OO design.
• Experience with microservices and RESTful APIs.
• Experience with AWS Lambda and SQS.
• Exposure to Cursor and Claude AI tools is a plus.
• Mentoring and training others on complex technical issues.
• Delivery of secure, well-tested and well-documented software.
• Experience with relational databases.

Skills

Java Spring

OOP design

Data structures

REST APIs

AWS Lambda

AWS SQS

Cursor/Claude

Mentoring

Security & testing

Relational DB

Distributed systems

Messaging: Kafka

Messaging: RabbitMQ

Streaming tools

Data warehousing basics

Tools

Kafka

RabbitMQ

Kinesis

Storm

Spark

Hadoop

Redshift

BigQuery

Job description

• Have a sound knowledge of a Java backend framework (e.g., Spring/Spring Boot), object

oriented design and design patterns, Data Structure.

• Have experience with microservices and implementing and consuming RESTful APIs.
• Have good experience in writing (High level design documents) HLDs and (Low level
• Experience in AWS- Lambda, SQS.
• Experience in AI tools – Cursor and/or Claude
• Experience mentoring and training others on complex technical issues
• Demonstrate a mindset of delivering secure, well-tested and well-documented software.
• Experience with relational databases.
• Excellent verbal and written communication.

Do You Know? (Skills good to have)

• Exposure to building service oriented distributed systems
• In building systems that process big data in a distributed environment, either in real time streaming or offline batching.
• In messaging systems like Kafka, RabbitMQ, kinesis, etc.
• In real time computation tools like Storm / Spark or Hadoop based tools.
• In Data warehousing technologies like Redshift, BigQuery, etc.