Senior Engineer

Responsibilities:

• Design, develop, and maintain RESTful APIs and microservices using Java (Spring Boot).
• Implement scalable and resilient backend solutions hosted on Azure or AWS Cloud.
• Collaborate with front-end engineers, data engineers, and DevOps teams to deliver end-to-end solutions.
• Optimise application performance by tuning database queries, caching, and load balancing strategies.
• Ensure security best practices for APIs, authentication, and authorisation (OAuth2 JWT, etc. ).
• Develop CI/CD pipelines using tools like Azure DevOps, GitHub Actions, or AWS CodePipeline.
• Work with containerization and orchestration tools (Docker, Kubernetes, ECS, AKS, EKS).
• Implement monitoring and logging using tools like CloudWatch, Azure Log Analytics, Azure Monitor, Datadog, or ELK.
• Design and implement event-driven architectures using Kafka, Azure Event Hubs, AWS Kinesis, or similar streaming platforms for real-time data processing and asynchronous communication.
• Build and maintain scalable message producers/consumers, ensuring reliable event processing, fault tolerance, retry mechanisms, and dead-letter queue (DLQ) handling.
• Participate in Agile/Scrum ceremonies, code reviews, and provide mentorship to junior developers.
• Ensure compliance with coding standards, best practices, and cloud-native architectures.

Requirements:

• Bachelor's or master's degree in computer science, Engineering, or a related field.
• 6-9 years of backend development experience.
• Strong expertise in Java (Spring Boot) or Golang for building microservices and APIs.
• Hands-on experience with Azure (Functions, AKS, ADLS, Cosmos DB, Service Bus) or AWS (Lambda, ECS, S3 DynamoDB, SQS/SNS, RDS, API Gateway).
• Strong knowledge of REST APIs, gRPC, and event-driven architecture.
• Experience with SQL/NoSQL databases (PostgreSQL, MySQL, MongoDB, DynamoDB, Cosmos DB).
• Proficiency in CI/CD pipelines, version control (Git), and Infrastructure as Code (Terraform, CloudFormation, ARM templates).
• Familiarity with observability tools (Grafana, Datadog, ELK stack, Cloud-native monitoring).
• Hands-on experience with Kafka consumer groups, partitioning, offsets, schema management, and stream processing concepts for building high-throughput, low-latency distributed systems.
• Understanding of message brokers/streaming platforms (Kafka, Kinesis, Event Hub).
• Solid understanding of software engineering principles: OOP, design patterns, and system design.

Nice to Have:

• Experience with serverless architectures (AWS Lambda / Azure Functions).
• Exposure to DevSecOps practices and cloud security.
• Familiarity with GraphQL or API gateways (Kong, Apigee, API Management).
• Knowledge of Data Engineering / Big Data tools (Spark, Databricks, Glue) is a plus.