Lead Engineering Manager

- Lead the architecture, design, and implementation of real-time data processing pipelines using Apache Flink . - Develop and maintain high-performance backend services and distributed systems using Java . - Design scalable event-driven architectures capable of handling high-throughput and low-latency workloads. - Optimize streaming jobs for performance, fault tolerance, and resource efficiency. - Ensure best practices in code quality, testing, observability, and CI/CD processes. - Collaborate with data engineering, DevOps, and product teams to define technical roadmaps and system requirements. - Conduct design reviews, troubleshoot production issues, and implement long-term reliability improvements. - Mentor and guide engineers, fostering a culture of technical excellence and continuous improvement. - Contribute to infrastructure decisions related to distributed processing, cloud deployment, and containerized environments.

- 10-12 years of overall experience in software engineering, with significant exposure to distributed systems. - Strong hands-on expertise in Apache Flink , including stream processing concepts such as windowing, state management, checkpoints, and event-time processing. - Advanced proficiency in Java , including concurrency, multithreading, memory management, and performance tuning. - Deep understanding of data streaming architectures and real-time processing frameworks. - Experience working with messaging systems (e.g., Kafka or similar platforms). - Strong knowledge of data structures, algorithms, and system design principles. - Experience deploying and managing applications in cloud environments (AWS, Azure, or GCP). - Familiarity with containerization technologies such as Docker and orchestration tools like Kubernetes. - Solid understanding of CI/CD pipelines, automated testing frameworks, and monitoring tools. - Experience with SQL and NoSQL databases in high-scale environments.

- Proven experience leading engineering teams or owning major technical initiatives. - Strong architectural decision-making abilities with a focus on scalability and maintainability. - Excellent problem-solving and analytical skills. - Ability to communicate complex technical concepts to both technical and non-technical stakeholders. - Strong ownership mindset and commitment to delivering high-quality solutions.

- Experience with big data ecosystems and real-time analytics platforms. - Exposure to performance benchmarking and capacity planning. - Experience working in Agile/Scrum environments.