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Flink Leader

Weekday AI
Posted 4 months ago, valid for 12 days
Salary

Competitive

Contract type

Full Time

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Sonic Summary

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  • We are looking for a Flink Leader with a minimum of 8 years of experience to drive real-time data processing solutions in the United States.
  • The ideal candidate should have deep expertise in Apache Flink, strong Java programming skills, and proven leadership experience managing engineering teams.
  • This full-time role involves architecting streaming platforms, enabling real-time analytics, and mentoring engineers while ensuring technical excellence.
  • Candidates should possess a strong understanding of distributed systems, real-time data processing, and experience with messaging systems like Kafka.
  • The position offers a competitive salary, commensurate with experience, within the range of 8 to 18 years in IT and data engineering.

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.

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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