Company
Technology
LeadDataPlatformEngineer
Neural analysis suggests this role is
optimal for Lead candidates.
“Lead Data Platform Engineer. Skills: Data Platform Engineering, Cloud Engineering, GCP, Go. Own data platform roadmap. Drive strategic decisions”
Industry & Context.
Problem-solving; Incident analysis
What They're Looking For.
Must Have
5+ years experience, Proficiency in Go (Golang), Extensive GCP experience, Advanced SQL skills, Solid analytical data modeling, Large-scale data processing architectures, Infrastructure-as-code experience, CI/CD pipeline experience, Containerized workload experience, Modern cloud deployment experience, Implement monitoring best practices, Implement observability best practices, Implement reliability best practices, Implement operational best practices, Practical AI coding assistant experience, Evaluate AI-generated code, Excellent communication skills, Excellent stakeholder management skills, Fluent German (C1 level), Good English communication skills, Problem-solving abilities, Ownership mindset, Proactive approach to technical leadership
Nice to Have
Familiarity with SQLMesh, Familiarity with dbt, Familiarity with comparable data transformation frameworks, Knowledge of Protobuf, Knowledge of comparable schema definition technologies, Knowledge of comparable data serialization technologies, Understanding of web analytics, Understanding of audience measurement systems, Understanding of comparable 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
Ensure business-critical systems availability
Ensure business-critical systems performance
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
Technical documentation; International collaboration; Engage technical audiences; Engage non-technical audiences
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
Applying for this Lead Data Platform Engineer role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
How to Apply on Lever
- Lever uses a streamlined one-page form — apply in under 5 minutes.
- LinkedIn import works well; review parsed data before submitting.
- The cover letter field is optional but visible to reviewers — use it to differentiate.
- Referral codes from employees can significantly boost visibility of your application.
ANONYMOUS · UNFILTERED
What do employees actually say about this company?
Real rants from real employees. Read before you apply.