Remote Confluent Kafka Engineer

N Consulting Ltd
Edinburgh, UK
about 1 month ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source

Tech stack

Java (Programming Language) Amazon Web Services Audit Trail Microsoft Azure Big Data Cloud Computing Continuous Integration Data Warehousing DevOps Monitoring of Systems Python (Programming Language) Open Source Technology
+16 more
Role-Based Access Control Prometheus Cloudera Data Streaming Grafana Multi-Cloud Event Driven Architecture Data Lakes Kubernetes Data Lineage Apache Flink Apache Kafka Splunk Data Pipelines Docker Confluent

Job description

As a Confluent Consulting Engineer, you will be responsible for designing, developing, and maintaining scalable real-time data pipelines and integrations using Kafka and Confluent components. You will collaborate with data engineers, architects, and DevOps teams to deliver robust streaming solutions.

Requirements

5+ years of hands-on experience with Apache Kafka (any distribution: open-source, Confluent, Cloudera, AWS MSK, etc.)

Strong proficiency in Java, Python, or Scala

Solid understanding of event-driven architecture and data streaming patterns

Experience deploying Kafka on cloud platforms such as AWS, GCP, or Azure

Familiarity with Docker, Kubernetes, and CI/CD pipelines

Excellent problem-solving and communication abilities

Preferred:

Candidates with experience in Confluent Kafka and its ecosystem will be given preference:

Experience with Kafka Connect, Kafka Streams, KSQL, Schema Registry, REST Proxy, Confluent Control Center

Hands-on with Confluent Cloud services, including ksqlDB Cloud and Apache Flink

Familiarity with Stream Governance, Data Lineage, Stream Catalog, Audit Logs, RBAC

Confluent certifications (Developer, Administrator, or Flink Developer)

Experience with Confluent Platform, Confluent Cloud managed services, multi-cloud deployments, and Confluent for Kubernetes

Knowledge of data mesh architectures, KRaft migration, and modern event streaming patterns

Exposure to monitoring tools (Prometheus, Grafana, Splunk)

Experience with data lakes, data warehouses, or big data ecosystems

Personal

Besides the professional qualifications of the candidates we place great importance in addition to various forms personality profile. These include:

High analytical skills

A high degree of initiative and flexibility

High customer orientation

High quality awareness

Excellent verbal and written communication skills

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