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Flink Leader

Weekday AI

United States Remote permanent

Posted: May 8, 2026

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Quick Summary

We are seeking a highly experienced Flink Leader to drive the design, development, and delivery of large-scale real-time data processing solutions. This role is ideal for an experienced engineering professional with a proven track record of managing high-performing teams, strong Java programming skills, and expertise in Apache Flink.

Job Description

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.


Requirements:
Key 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.

Required Skills

• 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.

Good to Have Skills

• 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.

Experience & Qualifications

• 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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