saas. group
Technology
LeadDataPlatformEngineer
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“Lead Data Platform Engineer at saas. group. Skills: Data Platform Engineering, GCP, AI-native engineering. Own data platform roadmap. Drive roadmap execution”
What You'll Achieve.
Increase engineering speed; Increase engineering quality; Improve data quality controls; Strengthen monitoring; Strengthen alerting; Strengthen observability; Establish engineering standards
Industry & Context.
Risk identification; Improvement opportunities; Incident management; Root cause analysis
What They're Looking For.
Must Have
5+ years of experience in Data Engineering, 5+ years of experience in Data Platform Engineering, 5+ years of experience in Platform Engineering, Solid Go (Golang) proficiency, Hands-on experience with GCP Cloud Run, Hands-on experience with GCP Pub/Sub, Hands-on experience with GCP BigQuery, Hands-on experience with GCP Dataflow, Hands-on experience with GCP Cloud Storage, Hands-on experience with GCP Cloud SQL, SQL and analytical data modeling, Practical experience with Terraform, Practical experience with IaC, Practical experience with CI/CD pipelines, Practical experience with containerized workloads, Experience with Protobuf, Experience with comparable schema definition frameworks, Experience with comparable serialization frameworks, Experience with AI coding assistants, Experience with coding agents, Fluent German (C1), Good English
Nice to Have
Familiarity with SQLMesh, Familiarity with dbt-style orchestration tools, Experience with Docker, Experience with Cloud Run serverless, Experience with Protobuf or comparable schema definition, Experience with comparable serialization frameworks, Familiarity with IVW standards, Familiarity with OEWA standards, Familiarity with comparable digital audience measurement standards, Genuine interest in web analytics domain, Ability to ramp quickly in web analytics, Experience with Claude Code, Experience with Codex, Sound judgment in reviewing AI-generated code
What You'll Do.
Own data platform roadmap
Drive roadmap execution
Make architecture decisions
Manage day-to-day platform operations
Manage streaming processing
Manage batch aggregation
Manage reporting logic
Manage incident management
Improve GCP-native platform
Focus on cost efficiency
Focus on maintainability
Focus on business continuity
Collaborate with Product
Collaborate with Customer Success
Collaborate with Leadership
Translate business requirements
Drive AI-native engineering adoption
Establish standards for AI use
Work with external specialists
Establish internal ownership
How You'll Work.
Team & Collaboration
Cross-functional teams; Product teams; Customer Success teams; Leadership teams; External specialists
Communication Scope
Technical documentation; German; English
Process & Methodology
Roadmap planning
Full Job Description
This role is part of our INFOnline team, one of our exciting brands at saas.group. INFOnline powers digital audience measurement for the German and Austrian media industry. Our systems process billions of events and deliver the trusted reach and engagement metrics used by publishers, advertisers, agencies, IVW and OEWA. As part of saas.group, we have been modernizing our business-critical infrastructure and moving towards a fully cloud-native architecture on GCP. The major migration work is complete. Now we are looking for a strong technical owner to run, harden, scale and evolve the new platform. Profile Overview We’re looking for a technically deep, hands-on Lead Data Platform Engineer to take full ownership of INFOnline’s central data platform from raw event ingress through processing, aggregation, data modeling and reporting delivery. You will take ownership of a newly built GCP-native data platform as it moves from completed migration into long-term production operation, optimization and continuous evolution. This is not a role where you simply follow someone else’s roadmap. You will help define how the platform should mature: where we need stronger observability, better data quality controls, clearer ownership boundaries, improved documentation, cost efficiency and more scalable operating models. This is a hands-on technical leadership role. You will set technical direction, make architecture decisions, establish engineering standards, mentor others and still work close to the code and systems. On top of that, you will help drive AI-native engineering practices using coding agents, AI-assisted testing, documentation, refactoring and incident analysis to increase engineering speed and quality. Your immediate impact in the first 3-6 months will be: 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
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