Staff Software Engineer – Streaming

Overview

As a Staff Data Engineer in Checkout.com’s Data and AI Platform Team, you will shape a scalable, AI-powered data platform that serves hundreds of teams and petabyte-scale volumes. You’ll enable engineers to focus on business problems by handling data collection, storage, processing and deployment concerns. You’ll guide platform adoption across the org and drive impactful, data-driven outcomes. This role offers the chance to influence architecture and elevate how we enable event-driven use cases at scale.

Pay / Benefits

• hybrid working model
• three days in the office
• growth and ownership
• high-performance culture
• collaborative environment

Responsibilities

• Develop a high-availability, large-scale event streaming platform using Kafka and Flink
• Provide leadership, mentoring, and strategic influence across engineers and managers
• Create tooling and documentation to promote platform adoption and ease of publishing data and deploying streaming apps
• Build infrastructure enabling users to host, monitor, and deploy streaming applications
• Advise the tech organization to accelerate adoption of the platform and unlock event-driven use cases
• Translate requirements and architecture work into actionable plans
• Offer hands-on support for event-based systems, including incident triage and root cause analysis

Key requirements

• Strong background in data systems with a focus on owning and scaling event streaming platforms
• Proven ability to influence engineering organizations through clear communication
• Hands-on experience with stream technologies, especially Kafka; experience with Kinesis
• Experience designing and implementing stream processing with Flink
• Cloud experience (AWS: MSK, S3, Lambda, ECS, SNS)
• Kubernetes experience (self-hosted or cloud)
• SQL databases experience
• Docker, container deployment and management
• Infrastructure as code (Terraform or similar) and CI/CD pipelines
• Proficiency in Java or Python

• strong presentation and communication skills
• ability to influence across teams
• collaborative and proactive problem-solving
• Kafka
• Flink
• Kinesis

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