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Apache Flink Engineer

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Onsite

Apache Flink Engineer

Global Business Ser. 4u

Apache Flink Engineer

Skills

Big DataJavaKafkaScala

18 days ago

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Important information


Contract type:

Permanent

Location:

Kirkland, WA, USA

Work mode:

Onsite

Published on:

6 October 2026

What they need


Role: Apache Flink Engineer Start Date: ASAP Duration: 12 months Location: Kirkland, WA or Santa Clara, CA or San Diego, CA - Onsite role Candidates need to be local to one of the cities in the description or willing to relocate. Expenses will not be reimbursed

Please note these architects must demonstrate real cloud native experience at production and good understanding of tuning Flink workloads. Client would like to see better articulation on the solutions they built with Flink as and infrastructure.

Qualifications Bachelor’s degree in computer science, Engineering, or a related field.

Extensive experience as an hands-on architect in designing and implementing solutions using Apache Flink.

In-depth understanding of stream processing concepts and mechanisms, such as event time processing, state management, and fault tolerance within the Apache Flink ecosystem.

Proficient in Java or Scala programming languages with solid experience in developing high-performance, scalable software.

Demonstrated ability in designing and optimizing data pipelines and architecture for efficiency, reliability, and performance.

Familiarity with surrounding technologies, including Kafka, K8s and service mesh principles.

Strong analytical and problem-solving skills, capable of tackling complex data processing challenges.

Experience Proven track record of successful implementation of Apache Flink solutions in production environments.

Experience in building and optimizing big data processing systems, particularly those using Apache Flink.

Hands-on experience with continuous integration and deployment (CI/CD) practices for stream processing systems.

Prior experience in a similar architect role, demonstrating the ability to design and lead significant data processing projects.

History of working collaboratively in cross-functional teams to deliver high-quality stream processing capabilities.

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