Lead Data Platform Engineer (German Speaker) at Jobgether

, , Canada -

Full Time

Start Date

Immediate

Expiry Date

04 Oct, 26

Salary

0.0

Posted On

06 Jul, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Go (Golang), Google Cloud Platform, SQL, Terraform, CI/CD, Docker, Protobuf, Data Modeling, BigQuery, Dataflow, Pub/Sub, Cloud Run, German Fluency, AI-Assisted Engineering, Platform Architecture, Stakeholder Management

Industry

Internet Marketplace Platforms

Description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Lead Data Platform Engineer (German Speaker) based in Canada. 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. It is ideal for engineers who enjoy solving complex technical challenges while mentoring others and driving technical excellence. \n 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. \n 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. We appreciate your interest and wish you the best! Why Apply Through Jobgether? 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. #LI-CL1

Responsibilities

Lead the strategy, architecture, and operational roadmap of a large-scale, cloud-native data platform. Drive continuous optimization of data pipelines and implement AI-native engineering practices to improve productivity.