Lead the full lifecycle of the data platform, from strategic planning to daily operational execution
Manage all aspects of data flow, including ingestion, real-time processing, batch computation, modeling, quality assurance, distribution, and reporting
Maintain high system reliability, scalability, and performance through robust monitoring, observability, and incident response
Advance the Google Cloud-native platform by prioritizing stability, cost optimization, maintainability, and resilience
Partner with Product, Customer Success, and leadership teams to convert business needs into durable technical implementations
Promote the adoption of AI-powered development tools across coding, testing, documentation, refactoring, and code review, while defining safe usage standards
Engage external experts when necessary while ensuring long-term internal ownership of core platform systems

Minimum of five years in data engineering, data platform development, or platform engineering within production environments
Proficiency in Go (Golang) is mandatory; core systems such as data collectors, Pub/Sub processors, Dataflow jobs, and CLI tools are built in Go
Extensive hands-on experience with Google Cloud services including Cloud Run, Pub/Sub, BigQuery, Dataflow, Cloud Storage, and Cloud SQL
Strong command of SQL and analytical data modeling techniques
Proven experience with infrastructure-as-code (Terraform), CI/CD pipelines, and containerized applications using Docker, particularly serverless workloads on Cloud Run
Experience working with Protobuf or similar schema and serialization frameworks
Fluent German language skills (C1 level); functional English proficiency for technical documentation and cross-team collaboration

Familiarity with SQLMesh or comparable data transformation and orchestration tools like dbt is highly advantageous
Knowledge of IVW, OEWA, or similar digital audience measurement standards, or a strong interest in web analytics with the ability to quickly contribute
Hands-on experience with AI coding assistants (e.g., Claude Code, Codex) and sound judgment in evaluating AI-generated code for quality, security, and operational safety

Fully remote work with no geographic restrictions
High degree of autonomy in problem-solving within a trust-based team culture
Minimal administrative overhead and meeting load to maintain productivity and momentum
Collaborative and supportive small team environment with a positive, engaging culture
Access to a network of entrepreneurial SaaS professionals for knowledge sharing and peer collaboration

Remote (Worldwide)

High-trust, low-bureaucracy environment with a focus on sustainable productivity and peer support

Fluent German (C1) required
Good English for technical documentation and internal collaboration
100% remote work
High-trust team environment with minimal bureaucracy
Opportunity to work with AI-native engineering practices including AI-assisted coding, testing, documentation, refactoring and incident analysis

saas.group is hiring a Lead Data Platform Engineer (German Speaker)