Lead architecture and delivery of real-time stream-processing pipelines using Apache Flink and Java. Design scalable, event-driven, low-latency systems; optimize performance and reliability; deploy and manage cloud/containerized services; enforce CI/CD, testing, and observability; troubleshoot production issues; collaborate with cross-functional teams; and mentor engineering teams.
This role is for one of the Weekday's clients
Min Experience: 10 years
Location: USA
JobType: full-time
As a Lead Engineering Manager, you will play a pivotal role in architecting and delivering complex stream-processing solutions, mentoring engineering teams, and collaborating closely with cross-functional stakeholders to translate business requirements into robust technical systems.
RequirementsKey Responsibilities
- 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.
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