Company
Technology
LeadDataPlatformEngineer
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“Lead Data Platform Engineer. Skills: Data Platform Engineering, Cloud-native platform, Google Cloud Platform, Data lifecycle management. Own data platform roadmap. Drive strategic decisions”
Industry & Context.
Problem-solving abilities
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, Proficiency in Go (Golang), Experience developing backend systems, Experience maintaining backend systems, Experience developing data processing applications, Experience maintaining data processing applications, Extensive experience with Google Cloud Platform services, Advanced SQL skills, Solid expertise in analytical data modeling, Solid expertise in large-scale data processing architectures, Experience with infrastructure-as-code, Experience with Terraform, Experience with CI/CD pipelines, Experience with containerized workloads, Experience with modern cloud deployment methodologies, Experience implementing monitoring, Experience implementing observability, Experience implementing reliability, Experience implementing operational best practices, Fluent German (C1 level), Good English communication skills
Nice to Have
Familiarity with SQLMesh, Familiarity with dbt, Knowledge of Protobuf, Understanding of web analytics, Understanding of audience measurement systems, Understanding of large-scale data environments
What You'll Do.
Own data platform roadmap
Drive strategic decisions
Drive execution across architecture
Drive execution across operations
Drive execution across improvement initiatives
Take responsibility for data lifecycle
Manage data ingestion
Manage streaming processing
Manage batch processing
Manage quality assurance
Manage delivery pipelines
Lead platform optimization
Focus on maintainability
Focus on operational efficiency
Focus on cost management
Establish monitoring processes
Establish observability processes
Establish alerting processes
Establish incident response processes
Conduct platform assessments
Identify technical risks
Identify improvement opportunities
Develop pragmatic roadmaps
Define engineering standards
Promote engineering standards
Collaborate with product teams
Collaborate with customer-facing teams
Collaborate with leadership teams
Translate business objectives
Drive adoption of AI practices
Provide technical leadership
Ensure sustainable ownership
How You'll Work.
Team & Collaboration
Product teams; Customer-facing teams; Leadership teams; Cross-functional teams
Communication Scope
Stakeholder management; Technical communication; Non-technical communication
Process & Methodology
Roadmap planning
Full Job Description
## Accountabilities Own the end-to-end data platform roadmap, driving strategic decisions and execution across architecture, operations, and continuous improvement initiatives. Take responsibility for the complete data lifecycle, including data ingestion, streaming and batch processing, data modeling, quality assurance, reporting, and delivery pipelines. Lead the ongoing optimization of a cloud-native platform, focusing on reliability, scalability, maintainability, operational efficiency, and cost management. Establish and strengthen monitoring, observability, alerting, and incident response processes to ensure business-critical systems remain highly available and performant. Conduct platform assessments, identify technical risks and improvement opportunities, and develop pragmatic roadmaps for platform evolution. Define and promote engineering standards covering documentation, testing, code reviews, infrastructure management, and operational excellence. Collaborate closely with product, customer-facing, and leadership teams to translate business objectives into scalable technical solutions. Drive the adoption of AI-assisted engineering practices, including coding, testing, documentation, refactoring, and incident analysis workflows. Mentor team members, provide technical leadership, and ensure sustainable ownership of critical platform components and processes. Requirements Minimum of 5 years of experience in Data Engineering, Data Platform Engineering, Platform Engineering, or related roles within production environments. Strong proficiency in Go (Golang) with hands-on experience developing and maintaining backend systems and data processing applications. Extensive experience with Google Cloud Platform services, including Cloud Run, Pub/Sub, BigQuery, Dataflow, Cloud Storage, and Cloud SQL. Advanced SQL skills and solid expertise in analytical data modeling and large-scale data processing architectures. Experience with infrastructure-as-code practices using Terraf
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