Global Business Ser. 4u
Kafka / Flink Engineer - Onsite
Skills
21 days ago
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Important information
Contract type:
Permanent
Location:
New York, NY, USA
Work mode:
Onsite
Published on:
7 October 2026
What they need
Job Title: Kafka / Flink Engineer Location: NYC, NY || Fortmill, SC - On-Site Priority: Critical Job Description We are looking for a Kafka / Flink Engineer to design, build, and support real-time streaming data platforms. The ideal candidate will have strong hands-on experience with Apache Kafka and Apache Flink, and a solid understanding of distributed systems, stream processing, and data pipelines in production environments.
Key Responsibilities
- Design, develop, and maintain real-time data streaming solutions using Apache Kafka and Apache Flink
- Build and optimize Kafka producers, consumers, topics, and stream processing applications
- Develop stateful and stateless Flink jobs for real-time analytics and event processing
- Ensure high availability, fault tolerance, and scalability of streaming platforms
- Monitor, troubleshoot, and resolve performance and reliability issues in production
- Collaborate with data engineers, platform teams, and application teams to integrate streaming solutions
- Implement data quality, security, and governance best practices
- Participate in code reviews, design discussions, and technical documentation
Required Skills & Qualifications
- Strong hands-on experience with Apache Kafka (Kafka Streams, Connect, Schema Registry)
- Solid experience with Apache Flink for real-time stream processing
- Strong programming skills in Java or Scala (Python is a plus)
- Experience working with distributed systems and event-driven architectures
- Knowledge of message serialization formats (Avro, Protobuf, JSON)
- Experience with monitoring and logging tools for streaming systems
- Good understanding of data modeling and streaming data patterns
Preferred / Nice To Have
- Experience with cloud platforms (AWS, Azure, or GCP)
- Knowledge of containerization and orchestration (Docker, Kubernetes)
- Experience with CI/CD pipelines for data platforms
- Exposure to other streaming tools such as Spark Streaming or Pulsar
- Understanding of security, authentication, and authorization in Kafka ecosystems
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