Lead Data Platform Engineer (German Speaker)

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Lead Data Platform Engineer (German Speaker) based in United States.

This is an outstanding opportunity for an experienced data platform engineer to lead the evolution of a large-scale, cloud-native data platform supporting business-critical analytics and reporting. In this hands-on technical leadership role, you will own the platform's architecture, operations, and long-term roadmap while driving continuous improvements in scalability, reliability, and data quality. You will work closely with cross-functional teams to transform business requirements into robust technical solutions and establish engineering best practices across the platform. Combining strategic decision-making with hands-on development, you will also champion AI-assisted engineering workflows to accelerate productivity and innovation. The position offers significant ownership, autonomy, and the opportunity to shape the future of a modern data ecosystem operating at massive scale. It is ideal for engineers who enjoy solving complex technical challenges while mentoring others and driving technical excellence.

• Own the end-to-end data platform strategy, architecture, and operational roadmap from data ingestion through reporting and analytics delivery.
• Lead the continuous optimization of a cloud-native data platform, focusing on reliability, scalability, performance, maintainability, and cost efficiency.
• Oversee data ingestion, streaming pipelines, batch processing, data modeling, quality assurance, and reporting workflows.
• Strengthen platform observability through comprehensive monitoring, alerting, incident management, and operational best practices.
• Define engineering standards for documentation, testing, code reviews, infrastructure management, and AI-assisted software development.
• Drive the adoption of AI-native engineering practices, including AI-powered coding, testing, refactoring, documentation, and code quality reviews.
• Collaborate closely with product, customer-facing teams, leadership, and external specialists to deliver scalable, business-focused technical solutions.
• Mentor engineers, provide technical leadership, and establish sustainable ownership across critical platform components.

Requirements

• 5+ years of experience in Data Engineering, Data Platform Engineering, Platform Engineering, or a closely related field.
• Strong hands-on experience designing and operating production-grade cloud-native data platforms.
• Solid proficiency in Go (Golang) for developing and maintaining backend services and data processing systems.
• Extensive experience with Google Cloud Platform services, including Cloud Run, Pub/Sub, BigQuery, Dataflow, Cloud Storage, and Cloud SQL.
• Strong SQL skills and experience with analytical data modeling; familiarity with SQLMesh, dbt, or similar orchestration frameworks is an advantage.
• Practical experience with Infrastructure as Code using Terraform, CI/CD pipelines, Docker, and serverless deployment models.
• Experience with Protobuf or comparable schema definition and serialization technologies.
• Familiarity with digital audience measurement, web analytics, or related data domains is desirable.
• Experience using AI coding assistants and the ability to review AI-generated code with attention to quality, security, and operational reliability.
• Excellent communication and stakeholder management skills.
• Fluent German (C1 level) is required, along with good English communication skills for technical collaboration and documentation.

Benefits

• Fully remote position with flexible working arrangements.
• High levels of autonomy and ownership in a trusted engineering environment.
• Opportunity to lead the evolution of a modern, large-scale cloud-native data platform.
• Minimal bureaucracy with an emphasis on efficient collaboration and sustainable delivery.
• Collaborative, supportive, and international engineering team.
• Access to a broad network of SaaS professionals, technical leaders, and knowledge-sharing opportunities.
• Transparent, location-adjusted compensation shared prior to the interview process.
• Strong opportunities for technical leadership, professional growth, and continuous learning.