Software Development Engineer - Backend Technologies

Job Description :

We are looking for a Backend Developer (SDE) with strong data engineering exposure to join our engineering team. In this role, you will be responsible for designing, building, and maintaining high-performance backend microservices and large-scale data processing pipelines.

The ideal candidate will have robust problem-solving skills, deep technical hands-on experience in Java, Scala, or Kotlin, and practical experience with Apache Spark or PySpark for distributed data processing.

Key Responsibilities :

• Backend Development: Design, develop, and maintain high-throughput, low-latency microservices and scalable RESTful APIs.

• Data Processing & Pipelines: Architect, build, and optimize large-scale batch and real-time data processing workflows using Apache Spark / PySpark.

• Distributed Systems: Work on high-volume, distributed computing architectures to ensure high availability, fault tolerance, and efficiency.

• Integration: Seamlessly integrate backend services with data lakes, data processing pipelines, and third-party systems.

• Performance Tuning: Optimize application logic, database queries, and distributed data processing engine configs for maximum speed and scalability.

• Quality & Engineering Standards: Follow engineering best practices including unit/integration testing, CI/CD automation, code reviews, and low-level/high-level system design.

• Cross-Functional Collaboration: Partner with data engineers, product managers, and infrastructure teams to deliver resilient, end-to-end features.

Key Requirements :

• Experience: 5 to 9 years of hands-on experience in core backend engineering and data processing.

• Core Programming: Strong, hands-on programming expertise in Java, Scala, or Kotlin.

• Distributed Computing: Practical, hands-on experience with Apache Spark or PySpark in a production environment.

• Frameworks & Architecture: Good command of Spring Boot / Microservices architecture, REST APIs, and asynchronous message queues (e.g., Kafka/RabbitMQ).

• Computer Science Fundamentals: Deep understanding of Data Structures, Algorithms, Multi-threading, and Object-Oriented / Functional Programming principles.

• Data Engineering Exposure: Solid grasp of ETL/ELT pipeline design, data modeling, and handling high-volume datasets.

Good to Have / Desired Skills :

• Experience with Google Cloud Platform (GCP) or other major cloud providers (AWS / Azure). (GCP preferred)

• Hands-on experience with containerization and orchestration tools like Docker and Kubernetes.