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Construction & Engineering
11-50
Founded 2020

Description

  • Lead the architecture, development, and optimization of real-time streaming applications using Apache Flink.
  • Design scalable, fault-tolerant distributed systems for high-volume data streams.
  • Manage and mentor engineering teams to maintain technical excellence and continuous learning.
  • Drive end-to-end delivery from requirements analysis and solution design through development, deployment, and production support.
  • Collaborate with product managers, architects, DevOps teams, and business stakeholders on aligned technical solutions.
  • 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 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.

Requirements

  • 8 to 18 years of overall IT experience with significant expertise in data engineering and streaming technologies.
  • Strong hands-on expertise in Apache Flink and stream processing architectures.
  • Excellent Java programming experience with a 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.
  • Experience working in Agile and fast-paced engineering environments.
  • Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.
  • Experience with Spark, Hadoop, or other big data technologies is preferred.
  • Exposure to cloud platforms such as AWS, Azure, or GCP is preferred.
  • Knowledge of containerization and orchestration tools like Docker and Kubernetes is preferred.
  • Experience with CI/CD pipelines and DevOps practices is preferred.
  • Familiarity with monitoring and observability tools is preferred.
  • Demonstrated experience leading enterprise-scale real-time data platform implementations.

Interested in this position?

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