Senior Java Developer

Design, implement, and maintain high-performance, low-latency messaging and processing components (Java-based) for real-time trading data.
Develop and operate resilient microservices and streaming pipelines using Kafka and related technologies.
Build and optimize storage and access patterns with modern databases (e.g., RocksDB, MongoDB, MemSQL/SingleStore) for real-time analytics.
Lead efforts to improve SDLC, testing (shift-left), configuration, and developer experience (CI/CD, automation, tooling).
Architect and implement observability frameworks: metrics, tracing (Tempo/Jaeger), logging, and alerting for highly available systems.
Collaborate with Platform/Cloud-native teams to design Kubernetes-based deployments, scalability, and disaster recovery strategies.
Implement backpressure, idempotency, retries with exponential backoff and jitter, circuit breakers, and fault-tolerant patterns.
Provide technical leadership, mentorship, and code reviews; communicate effectively with stakeholders across teams.
Participate in on-call rotations and incident response, driving root-cause analysis and post-mortems.

Requirements:

8+ years of professional software development, with a strong emphasis on Java and distributed systems.
Deep hands-on experience building large-scale, low-latency, high-throughput systems.
Expertise with messaging and streaming technologies, especially Kafka (producers/consumers, transactions, exactly-once processing).
Proficiency with data stores used in real-time contexts (RocksDB, MongoDB, MemSQL/SingleStore) and time-series considerations.
Solid understanding of concurrency, memory models, locking vs. lock-free approaches, and performance tuning in Java.
Experience designing and operating in Kubernetes-based environments; familiarity with cloud-native patterns, DevOps, and observability tooling.
Strong problem-solving, debugging, and performance profiling skills.
Excellent communication, collaboration, and leadership capabilities.
Bonus: Python scripting experience; knowledge of Prometheus/Grafana, Tempo/Jaeger, and cloud platforms (AWS/GCP/Azure).

Nice-to-Have

Experience with front-to-back architectural patterns in trading or financial services.
Knowledge of, or experience with, RocksDB, distributed caches, and columnar stores.
Familiarity with time-series data modeling and windowed computations.
Exposure to risk monitoring, market data feeds, and post-trade workflows.

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