Lead architecture, development, and delivery of enterprise-scale real-time streaming solutions using Apache Flink and Java. Manage and mentor engineering teams, design fault-tolerant distributed systems, implement stream processing pipelines, and ensure performance, scalability, and production reliability. Collaborate with stakeholders across product, DevOps, and architecture to drive technical roadmaps and best practices.
This role is for one of the Weekday's clients
Min Experience: 8 years
Location: United States
JobType: full-time
We are seeking an experienced and dynamic Flink Leader to drive the design, development, and delivery of large-scale real-time data processing solutions. The ideal candidate will have deep expertise in Apache Flink, strong Java programming skills, and proven leadership experience managing high-performing engineering teams. This role requires a strategic thinker who can lead complex streaming data initiatives while collaborating closely with cross-functional stakeholders to deliver scalable, reliable, and high-performance solutions.
As a Flink Leader, you will play a critical role in architecting next-generation streaming platforms and enabling real-time analytics capabilities for enterprise-scale applications. You will mentor engineers, define technical roadmaps, establish best practices, and ensure the successful execution of data engineering projects.
RequirementsKey Responsibilities
- Lead the architecture, development, and optimization of real-time streaming applications using Apache Flink.
- Design scalable and fault-tolerant distributed systems capable of handling high-volume data streams.
- Manage and mentor engineering teams, ensuring technical excellence, collaboration, and continuous learning.
- Drive end-to-end project delivery including requirement analysis, solution design, development, deployment, and production support.
- Collaborate with product managers, architects, DevOps teams, and business stakeholders to define technical solutions aligned with organizational goals.
- Develop robust applications and services using Java and modern backend engineering practices.
- Implement data processing pipelines, stream analytics, event-driven architectures, and real-time monitoring solutions.
- Ensure system reliability, scalability, performance tuning, and operational efficiency across distributed environments.
- Establish coding standards, review code quality, and promote engineering best practices.
- Lead troubleshooting and root-cause analysis for production issues in streaming and distributed systems.
- Contribute to technology strategy, innovation initiatives, and continuous platform improvements.
- Support hiring, team building, and capability development for streaming data engineering teams.
- Strong hands-on expertise in Apache Flink and stream processing architectures.
- Excellent programming experience in Java with strong understanding of multithreading, concurrency, and distributed systems.
- Proven experience leading engineering teams and managing large-scale technical programs.
- Strong knowledge of real-time data processing, event streaming, and microservices architecture.
- Experience with distributed messaging systems such as Kafka.
- Understanding of big data ecosystems and cloud-native technologies.
- Expertise in performance optimization, scalability, and high-availability system design.
- Strong problem-solving, stakeholder management, and communication skills.
- Experience working in Agile and fast-paced engineering environments.
- Experience with Spark, Hadoop, or other big data technologies.
- Exposure to cloud platforms such as AWS, Azure, or GCP.
- Knowledge of containerization and orchestration tools like Docker and Kubernetes.
- Experience with CI/CD pipelines and DevOps practices.
- Familiarity with monitoring and observability tools.
- 8 to 18 years of overall IT experience with significant expertise in data engineering and streaming technologies.
- Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.
- Demonstrated experience leading enterprise-scale real-time data platform implementations.
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