Lead Data Platform Engineer

Role Overview

• Audit and map the existing cloud and data platform architecture identify critical risks, dependencies, and improvement opportunities
• Take ownership of core platform components from data ingress to reporting, supported by structured knowledge transfer where needed
• Establish full internal ownership of the new cloud-native data platform
• Improve data quality controls, validation processes and operational safeguards
• Build a pragmatic post-migration roadmap focused on stability, scalability, data quality, cost efficiency and business continuity
• Strengthen monitoring, alerting, and observability for business-critical data workflows and IVW/OEWA delivery pipelines
• Own the end-to-end data platform roadmap and drive its execution from architecture decisions to day-to-day platform operations
• Take accountability for data ingress, streaming processing, batch aggregation, data modeling, quality, delivery and reporting logic
• Ensure reliability, scalability and performance through strong monitoring, observability and incident management practices
• Continuously improve the new GCP-native platform with a focus on stability, cost efficiency, maintainability and business continuity
• Collaborate closely with Product, Customer Success and Leadership to translate business requirements into scalable technical solutions
• Drive AI-native engineering adoption, including AI-assisted coding, refactoring, testing, documentation and code reviews and establish standards for safe, effective use
• Work with external specialists where useful and establish sustainable internal ownership of all critical platform components

Requirements

• 5+ years of experience in Data Engineering, Data Platform Engineering, or Platform Engineering in production environments
• Solid Go (Golang) proficiency is required. Our core backend systems, including ingress collectors, Pub/Sub processors, Dataflow jobs, batch loaders, controllers and CLI tools are written in Go.
• Strong hands-on experience with GCP Cloud Run, Pub/Sub, BigQuery, Dataflow, Cloud Storage, Cloud SQL
• Strong SQL and analytical data modeling skills; familiarity with SQLMesh (or similar dbt-style orchestration tools) is a significant plus
• Practical experience with Terraform / IaC, CI/CD pipelines, and containerized workloads (Docker; Cloud Run-style serverless, not cluster Kubernetes)
• Experience with Protobuf or comparable schema definition and serialization frameworks
• Familiarity with IVW, OEWA or comparable digital audience measurement standards or a genuine interest in the web analytics domain and the ability to ramp quickly
• Experience with AI coding assistants and coding agents (Claude Code, Codex, or similar) and sound judgment in reviewing AI-generated code for quality, security, and operational risk
• Excellent communication skills with both technical and non-technical stakeholders
• Fluent German (C1) required; good English for technical documentation and saas.group collaboration.

Tech Stack

• BigQuery
• Cloud
• Docker
• Google Cloud Platform
• Kubernetes
• SQL
• Terraform
• Go

Benefits

• Ultimate flexibility: We’re 100% remote. You can work from wherever you like, whenever you like.
• Freedom and autonomy: We’re a high-trust team, and you’ll be given lots of flexibility to solve problems in your own way, with plenty of help from the team when you need it.
• Minimum bureaucracy: We don’t like to get bogged down with meetings and red tape. We like to be efficient and keep momentum steady & sustainable.
• Small & friendly team: We help each other out, have fun, and joke around.
• Our network: We are a community of entrepreneurial SaaS professionals that regularly exchange ideas, knowledge, learning and expertise with each other internally.