We are seeking a seasoned and technically adept individual to join our engineering team. In this role, you will be responsible for the architectural integrity and technical excellence of MPL's platform, ensuring it remains scalable, available, reliable, and maintainable. You will play a key role in designing and delivering mission-critical features while collaborating with cross-functional teams.
Responsibilities :
- Ensure the platform's architecture meets the highest standards of scalability, availability, and reliability.
- Contribute as both a technical leader and a hands-on developer.
- Own end-to-end performance and availability of features; drive rapid product innovation while ensuring service reliability.
- Collaborate with Program Managers, Product Managers, the Reliability and Continuity Engineering (RCE) team, and the Quality Engineering (QE) team to independently estimate and execute tasks.
- Maintain and drive the execution of the technical backlog for non-functional platform requirements.
- Participate in release planning, prioritizing work based on technical feasibility and engineering constraints.
- Continuously seek opportunities to improve architecture, design, delivery timelines, and code quality.
Requirements :
Proven experience in building highly distributed, low-latency, and high-throughput systems.Minimum 6 years of hands-on experience in Java and Spring Boot, ideally in consumer-facing internet products.Proficiency in REST (Spring Boot, jHipster, Dropwizard) and non-REST (gRPC) communication paradigms.Experience with real-time data streaming technologies such as Kafka, Apache Spark, and Flink.Good to have : exposure to building Data Products or ML Platforms.Deep understanding of microservices architecture and principles (12-factor app) and related networking models.Strong background in cloud engineering, preferably with Google Cloud Platform (GCP).Proficient in Java and / or Python; strong code reviewer with a track record of writing high-quality, maintainable code.Familiarity with various data storage paradigms : relational, non-relational, document, graph, object, and time-series databases.Sound knowledge of CAP theorem, distributed transactions, and consistency models (transactional and eventual).Understanding of distributed system design patterns, including backpressure, bulkhead, circuit breaker, event sourcing, CQRS, and event-driven architecture.Experience with caching strategies for mid-tier services.Solid grasp of containerization, orchestration, and service mesh frameworks (e. g., Kubernetes, Mesos, Istio).Strong understanding of best practices in API design.Experience with architecting globally distributed systems with disaster recovery capabilities.Advocate of engineering excellence, including code reviews, unit testing, and documentation of system design and architecture.Bachelor's degree in Computer Science or an equivalent engineering discipline from a reputed institution.ref : hirist.tech)