Senior Data Streaming Platform Engineer

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In short
We are seeking a highly skilled and motivated Streaming Platform Engineer to join the Data Streaming Platform team. This is a unique hybrid role that combines the disciplines of platform , software , and data engineering to build, scale, and maintain our high-performance, real-time data streaming platform. The ideal candidate should have a passion for architecting robust, scalable systems to enable data-driven products and services at massive scale.
Your mission

• Design, build, and maintain the core infrastructure for our real-time data streaming platform, ensuring high availability, reliability, and low latency.
• Implement and optimize data pipelines and stream processing applications using technologies like Apache Kafka, Apache Flink, and Spark Streaming.
• Collaborate with software and data engineering teams to define event schemas, ensure data quality, and support the integration of new services into the streaming ecosystem.
• Develop and maintain automation and tooling for platform provisioning, configuration management and CI/CD pipelines.
• Champion the development of self-service tools and workflows that empower engineers to manage their own streaming data needs, reducing friction and accelerating development.
• Monitor platform performance, troubleshoot issues, and implement observability solutions (metrics, logging, tracing) to ensure the platform's health and stability.
• Stay up-to-date with the latest advancements in streaming and distributed systems technologies and propose innovative solutions to technical challenges.

Your story

• Streaming Platforms & Architecture: Strong production experience with Apache Kafka and its ecosystem (e.g., Confluent Cloud, Kafka Streams, Kafka Connect). Solid understanding of distributed systems and event-driven architectures and how they drive modern microservices and data pipelines.
• Real-Time Data Pipelines: Experience building and optimizing real-time data pipelines for ML, analytics and reporting, leveraging technologies such as Apache Flink, Spark Structured Streaming, and integration with low-latency OLAP systems like Apache Pinot.
• Platform Infrastructure & Observability: Hands-on experience with major Cloud Platforms (AWS, GCP, or Azure), Kubernetes and Docker, coupled with proficiency in Infrastructure as Code (Terraform). Experience integrating and managing CI/CD pipelines (GitHub Actions) and implementing comprehensive Observability solutions (New Relic, Prometheus, Grafana) for production environments.
• Programming Languages: Proficiency in at least one of the following: Python, Typescript, Java, Scala or Go.
• Data Technologies: Familiarity with data platform concepts, including data lakes and data warehouses.

Seniority level

Seniority level

• Not Applicable

Employment type

Employment type

• Full-time

Job function

Job function

• Engineering and Information Technology

Industries

Industries

• Retail

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