At BairesDev®, we've been leading the way in technology projects for over 15 years. We deliver cutting-edge solutions to giants like Google and the most innovative startups in Silicon Valley.
Our diverse 4,000+ team, composed of the world's Top 1% of tech talent, works remotely on roles that drive significant impact worldwide.
When you apply for this position, you're taking the first step in a process that goes beyond the ordinary. We aim to align your passions and skills with our vacancies, setting you on a path to exceptional career development and success.
As a Real-Time Data Engineer, you will design and build high-performance streaming pipelines to enable instant data availability. You will act as a key link between raw event sources and live analytical systems, ensuring that data flows reliably and securely at scale.
What You'll Do
Design and implement production-grade real-time data pipelines using Apache Kafka, Flink, or Kinesis.
Develop event-driven architectures to support low-latency data processing and sub-second decision-making.
Manage schema governance and evolution using schema registries to ensure data compatibility across systems.
Optimize streaming jobs for high throughput, fault tolerance, and exactly-once processing semantics.
Build and maintain robust integrations between event sources and downstream sinks using Java, Scala, or Python.
Collaborate with cross-functional teams to define real-time data standards and operational monitoring strategies.
What We Are Looking For
4+ years of experience in Data Engineering, Software Engineering, or Stream Processing.
Proven expertise in building real-time data pipelines using Apache Kafka, Flink, or Kinesis.
Proficiency in Java, Scala, or Python for developing event-driven applications.
Strong understanding of schema management, event-driven patterns, and data consistency.
Experience with cloud-based streaming services and distributed systems at scale.
Advanced proficiency in English.
How we do ma
📌 Real-Time Data Engineer (México)
🏢 BairesDev
📍 México
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