Senior Apache Kafka Developer — Real-Time Data

BairesDev; Ciudad de México; On-site; MXN 2,198,000 - 3,297,000; Full time

Benefits offered by this job

Competitive USD salary

Paid parental leave

Vacation & national holidays

Global multicultural environment

Mentorship & growth opportunities

Job summary

BairesDev seeks an Apache Kafka Developer to work on distributed data processing and real-time analytics. You will contribute to Kafka and related ecosystem projects, focusing on performance optimization and scalable architecture.

You will collaborate with global teams, build streaming analytics with Kafka Streams and Spark, and enhance Kafka cluster performance while ensuring robust deployment and integration.

Qualifications

• 10+ years of software development experience.
• Expertise in distributed systems and large-scale event streaming.
• Solid understanding of Apache Kafka architecture (topics, partitions, consumer groups).
• Proficiency in Java and Scala.
• Experience tuning performance of distributed systems at scale.
• Contributions to Apache open source projects (Kafka, Spark, Flink, or similar).
• Advanced level of English.

Responsibilities

• Contribute actively to Apache Kafka and related open source projects as a core contributor.
• Develop and optimize event streaming platforms for high-throughput message processing.
• Build streaming analytics capabilities using Kafka Streams and integration with Apache Spark.
• Enhance Kafka cluster performance, topic configurations, and producer/consumer optimization.
• Collaborate with engineering teams on system integration and deployment.

Skills

Java

Scala

Distributed systems

Kafka

Spark

Performance tuning

Open source

English

Tools

Kafka

Spark

Flink

Job description

BairesDev seeks an Apache Kafka Developer to work on distributed data processing and real-time analytics. You will contribute to Kafka and related ecosystem projects, focusing on performance optimization and scalable architecture.

You will collaborate with global teams, build streaming analytics with Kafka Streams and Spark, and enhance Kafka cluster performance while ensuring robust deployment and integration.