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.- Familiarity with modern CI/CD tools, monitoring, and observability frameworks (e.g., Prometheus, Grafana, ELK). (ref:hirist.tech)