Lead Data Platform Engineer

Accountabilities

• Own the end-to-end data platform roadmap, driving strategic decisions and execution across architecture, operations, and continuous improvement initiatives.
• Take responsibility for the complete data lifecycle, including data ingestion, streaming and batch processing, data modeling, quality assurance, reporting, and delivery pipelines.
• Lead the ongoing optimization of a cloud-native platform, focusing on reliability, scalability, maintainability, operational efficiency, and cost management.
• Establish and strengthen monitoring, observability, alerting, and incident response processes to ensure business-critical systems remain highly available and performant.
• Conduct platform assessments, identify technical risks and improvement opportunities, and develop pragmatic roadmaps for platform evolution.
• Define and promote engineering standards covering documentation, testing, code reviews, infrastructure management, and operational excellence.
• Collaborate closely with product, customer-facing, and leadership teams to translate business objectives into scalable technical solutions.
• Drive the adoption of AI-assisted engineering practices, including coding, testing, documentation, refactoring, and incident analysis workflows.
• Mentor team members, provide technical leadership, and ensure sustainable ownership of critical platform components and processes.

Requirements

• Minimum of 5 years of experience in Data Engineering, Data Platform Engineering, Platform Engineering, or related roles within production environments.
• Strong proficiency in Go (Golang) with hands-on experience developing and maintaining backend systems and data processing applications.
• Extensive experience with Google Cloud Platform services, including Cloud Run, Pub/Sub, BigQuery, Dataflow, Cloud Storage, and Cloud SQL.
• Advanced SQL skills and solid expertise in analytical data modeling and large-scale data processing architectures.
• Experience with infrastructure-as-code practices using Terraform, CI/CD pipelines, containerized workloads, and modern cloud deployment methodologies.
• Familiarity with SQLMesh, dbt, or similar data orchestration and transformation frameworks is highly desirable.
• Knowledge of Protobuf or comparable schema definition and data serialization technologies.
• Experience implementing monitoring, observability, reliability, and operational best practices in production systems.
• Understanding of web analytics, audience measurement systems, or comparable large-scale data environments is advantageous.
• Practical experience using AI coding assistants and the ability to evaluate AI-generated code for quality, security, and maintainability.
• Excellent communication and stakeholder management skills, with the ability to engage both technical and non-technical audiences.
• Fluent German (C1 level) and good English communication skills for documentation and international collaboration.
• Strong problem-solving abilities, ownership mindset, and a proactive approach to technical leadership.

Benefits

• Fully remote work environment with the flexibility to work from anywhere.
• High degree of autonomy and trust, allowing you to shape solutions and influence technical direction.
• Opportunity to take ownership of a modern cloud-native platform with significant business impact.
• Collaborative and supportive team culture focused on knowledge sharing and continuous improvement.
• Minimal bureaucracy and streamlined processes designed to maximize productivity and innovation.
• Access to a broad network of SaaS professionals for learning, collaboration, and professional development.
• Exposure to cutting-edge technologies, cloud platforms, AI-assisted engineering practices, and large-scale data systems.
• Inclusive and diverse workplace committed to equal opportunities and professional growth.
• Transparent compensation practices, with salary information shared during the hiring process.