Lead Data Platform Engineer (German Speaker)
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Key skills for this role
About the Role
Our partner is seeking a Lead Data Platform Engineer (German Speaker) to own the architecture, operations, and roadmap of a large-scale cloud-native data platform. The role involves leading optimization, mentoring engineers, and driving AI-assisted engineering practices.
Key Skills for This Role
Responsibilities
- Own the end to end data platform strategy, architecture, and operational roadmap from data ingestion through reporting and analytics delivery
- Lead continuous optimization of cloud native data platform focusing on reliability, scalability, performance, maintainability, and cost efficiency
- Oversee data ingestion, streaming pipelines, batch processing, data modeling, quality assurance, and reporting workflows
- Strengthen platform observability through comprehensive monitoring, alerting, incident management, and operational best practices
- Define engineering standards for documentation, testing, code reviews, infrastructure management, and AI assisted software development
- Drive adoption of AI native engineering practices including AI powered coding, testing, refactoring, documentation, and code quality reviews
- Collaborate closely with product, customer facing teams, leadership, and external specialists to deliver scalable, business focused technical solutions
- Mentor engineers, provide technical leadership, and establish sustainable ownership across critical platform components
Requirements
- 5+ years of experience in Data Engineering, Data Platform Engineering, Platform Engineering, or closely related field
- Strong hands on experience designing and operating production grade cloud native data platforms
- Solid proficiency in Go (Golang) for developing and maintaining backend services and data processing systems
- Extensive experience with Google Cloud Platform services (Cloud Run, Pub/Sub, BigQuery, Dataflow, Cloud Storage, Cloud SQL)
- Strong SQL skills and experience with analytical data modeling
- Practical experience with Infrastructure as Code using Terraform, CI/CD pipelines, Docker, and serverless deployment models
- Experience with Protobuf or comparable schema definition and serialization technologies
- Fluent German (C1 level) required, good English communication skills
- Experience using AI coding assistants and ability to review AI generated code
- Excellent communication and stakeholder management skills
Full Job Posting
Position Overview
- This is an outstanding opportunity for an experienced data platform engineer to lead the evolution of a large scale, cloud native data platform supporting business critical analytics and reporting.
- In this hands on technical leadership role, you will own the platform's architecture, operations, and long term roadmap while driving continuous improvements in scalability, reliability, and data quality.
- You will work closely with cross functional teams to transform business requirements into robust technical solutions and establish engineering best practices across the platform.
- Combining strategic decision making with hands on development, you will also champion AI assisted engineering workflows to accelerate productivity and innovation.
- The position offers significant ownership, autonomy, and the opportunity to shape the future of a modern data ecosystem operating at massive scale.
Accountabilities
- Own the end to end data platform strategy, architecture, and operational roadmap from data ingestion through reporting and analytics delivery.
- Lead the continuous optimization of a cloud native data platform, focusing on reliability, scalability, performance, maintainability, and cost efficiency.
- Oversee data ingestion, streaming pipelines, batch processing, data modeling, quality assurance, and reporting workflows.
- Strengthen platform observability through comprehensive monitoring, alerting, incident management, and operational best practices.
- Define engineering standards for documentation, testing, code reviews, infrastructure management, and AI assisted software development.
- Drive the adoption of AI native engineering practices, including AI powered coding, testing, refactoring, documentation, and code quality reviews.
- Collaborate closely with product, customer facing teams, leadership, and external specialists to deliver scalable, business focused technical solutions.
- Mentor engineers, provide technical leadership, and establish sustainable ownership across critical platform components.
Requirements
- 5+ years of experience in Data Engineering, Data Platform Engineering, Platform Engineering, or a closely related field.
- Strong hands on experience designing and operating production grade cloud native data platforms.
- Solid proficiency in Go (Golang) for developing and maintaining backend services and data processing systems.
- Extensive experience with Google Cloud Platform services, including Cloud Run, Pub/Sub, BigQuery, Dataflow, Cloud Storage, and Cloud SQL.
- Strong SQL skills and experience with analytical data modeling; familiarity with SQLMesh, dbt, or similar orchestration frameworks is an advantage.
- Practical experience with Infrastructure as Code using Terraform, CI/CD pipelines, Docker, and serverless deployment models.
- Experience with Protobuf or comparable schema definition and serialization technologies.
- Familiarity with digital audience measurement, web analytics, or related data domains is desirable.
- Experience using AI coding assistants and the ability to review AI generated code with attention to quality, security, and operational reliability.
- Excellent communication and stakeholder management skills.
- Fluent German (C1 level) is required, along with good English communication skills for technical collaboration and documentation.
Benefits
- Fully remote position with flexible working arrangements.
- High levels of autonomy and ownership in a trusted engineering environment.
- Opportunity to lead the evolution of a modern, large scale cloud native data platform.
- Minimal bureaucracy with an emphasis on efficient collaboration and sustainable delivery.
- Collaborative, supportive, and international engineering team.
- Access to a broad network of SaaS professionals, technical leaders, and knowledge sharing opportunities.
- Transparent, location adjusted compensation shared prior to the interview process.
- Strong opportunities for technical leadership, professional growth, and continuous learning.
How Jobgether Works
- We use an AI powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements.
- Our system identifies the top fitting candidates, and this shortlist is then shared directly with the hiring company.
- The final decision and next steps (interviews, assessments) are managed by their internal team.
Data Privacy Notice
- By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer.
- This processing is based on legitimate interest and pre contractual measures under applicable data protection laws (including GDPR).
- You may exercise your rights (access, rectification, erasure, objection) at any time.
- We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses.
- These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans.
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