platform engineer for AI data workflows

platform engineer for AI data workflows

Enfint | Greater London, ENG, GB

Posted a month ago

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Description

Описание

DeepL is a global AI product and research company focused on secure, intelligent solutions for complex business problems. Its Language AI platform provides human-like translation, improved writing, and real-time voice translation for individuals and businesses worldwide.

Задачи

  • Build and evolve data platform infrastructure, including the Databricks-based lakehouse, Kafka consumers, and foundational tooling for data engineers
  • Support and extend dlt to make data ingestion patterns reusable and robust
  • Make technical decisions that enable the platform to scale with DeepL’s data volume and use-case diversity
  • Build connectors, interfaces, and integrations that bring data to humans and AI agents, including MCP connectors and workflow skills
  • Design AI-powered data workflows for data engineers, analysts, business teams, and AI tools
  • Implement data observability, quality frameworks, monitoring, and alerting
  • Own infrastructure-as-code, CI/CD for data workflows, access management, security configurations, audit trails, and spend governance
  • Build golden-path templates and patterns that help engineers across the company use data safely and efficiently

Требования

  • Hands-on experience building and operating cloud-based data infrastructure
  • Experience with Terraform/Terragrunt, CI/CD for data workflows, and Docker/Kubernetes
  • Production-quality Python proficiency
  • Reliability mindset, including observability, meaningful alerts, production ownership, and incident-driven improvements
  • Platform-product mindset focused on developer experience and reducing friction for platform users
  • Communicates effectively across different audiences and actively uses feedback from data consumers
  • Actively uses AI-powered tools to move faster and focus on architecture, system design, and scalability tradeoffs
  • Nice to have: experience with Databricks, Apache Iceberg, Kafka, or similar lakehouse and streaming technologies

Условия

  • Hybrid work schedule with office attendance twice a week and flexible working hours
  • Virtual Shares for every employee
  • Regular in-person team events
  • Monthly full-day hacking sessions
  • 30 Days of annual leave excluding public holidays
  • Mental health resources
  • Competitive benefits tailored to the employee’s location
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