Lead Data Platform Engineer

Lead Data Platform Engineer

Company: saas.group (INFOnline team) Location: Remote (Europe) Employment Type: Permanent

About the Role

INFOnline, a brand within saas.group, is a leader in digital audience measurement for the German and Austrian media industry, processing billions of events to deliver trusted reach and engagement metrics. We are seeking a technically deep, hands-on Lead Data Platform Engineer to take full ownership of INFOnline’s central data platform. This newly built, GCP-native platform is moving from migration into long-term production operation, optimization, and continuous evolution.

This is a hands-on technical leadership role where you will define the platform's future, focusing on areas like observability, data quality, cost efficiency, and scalability. You will set technical direction, make architecture decisions, establish engineering standards, mentor others, and remain closely involved with the code and systems. Additionally, you will drive AI-native engineering practices to enhance engineering speed and quality.

Key Responsibilities

• Own the end-to-end data platform roadmap and drive its execution from architecture decisions to daily operations.
• Take accountability for data ingress, streaming processing, batch aggregation, data modeling, quality, delivery, and reporting logic.
• Ensure reliability, scalability, and performance through robust monitoring, observability, and incident management.
• Continuously improve the GCP-native platform, focusing on stability, cost efficiency, maintainability, and business continuity.
• Collaborate 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, establishing standards for safe and effective use.
• Work with external specialists where beneficial and establish sustainable internal ownership of all critical platform components.

Immediate Impact (First 3-6 Months)

• Audit and map the existing cloud and data platform architecture to identify risks, dependencies, and improvement opportunities.
• Take ownership of core platform components, from data ingress to reporting, with structured knowledge transfer.
• Establish full internal ownership of the new cloud-native data platform.
• Enhance 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 delivery pipelines.
• Establish engineering standards for documentation, code reviews, testing, and AI-native development practices.

Requirements

• 5+ years of experience in Data Engineering, Data Platform Engineering, or Platform Engineering in production environments.
• Solid Go (Golang) proficiency is required for core backend systems.
• Strong hands-on experience with GCP services: 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 / Infrastructure as Code (IaC), CI/CD pipelines, and containerized workloads (Docker; serverless focus).
• Experience with Protobuf or comparable schema definition and serialization frameworks.
• Familiarity with IVW, OEWA, or comparable digital audience measurement standards, or a strong interest and ability to learn quickly.
• Experience with AI coding assistants and coding agents (e.g., Claude Code, Codex) and sound judgment in reviewing AI-generated code.
• Excellent communication skills with both technical and non-technical stakeholders.
• Fluent German (C1) is required.
• Good English proficiency for technical documentation and collaboration.

What We Offer

• Ultimate Flexibility: 100% remote work, allowing you to work from anywhere, anytime.
• Freedom and Autonomy: A high-trust environment with flexibility to solve problems in your own way, with team support available.
• Minimum Bureaucracy: An efficient approach focused on maintaining steady and sustainable momentum.
• Small & Friendly Team: A collaborative environment where team members help each other, have fun, and foster a positive atmosphere.
• Our Network: Access to a community of entrepreneurial SaaS professionals for regular exchange of ideas, knowledge, and expertise.

saas.group is committed to creating a diverse and inclusive workplace. We offer fair and transparent pay, with location-adjusted salary ranges targeting local market medians for a remote-first environment. Salary details will be shared in writing before the first interview.