Top Tech Jobs & Startup Jobs

Manage and optimize large-scale Google Ads campaigns through data analysis, A/B testing, SQL, BI dashboards, competitor research, and automation. The role requires analyzing campaign performance, identifying growth opportunities, reporting insights to marketing and management, and improving workflows. Candidates need at least three years of Google Ads experience managing monthly budgets exceeding €300,000, strong SQL skills, and proficiency with Google marketing and analytics tools. Experience with additional advertising platforms, automation, and German is preferred.

Manage and optimize Google Ads campaigns, primarily Search and Performance Max, with a monthly budget of at least €100,000. Own campaign strategy, keyword and bidding decisions, ad copy testing, landing page concepts, CRO, and conversion optimization. Maintain Looker Studio dashboards and provide data-driven recommendations. Collaborate with IT, Design, Product, and Performance Marketing teams to improve lead generation and support international growth.

Build and deploy statistical, predictive, and AI models for pricing, matching, growth, and product decisions. Develop LLM and RAG features, evaluate AI quality, design experiments, analyze user funnels, and improve supply-demand matching. Partner with performance marketing on targeting and attribution, define KPIs, create AWS QuickSight dashboards, document work in Jira, and communicate recommendations through implementation.

Own the end-to-end matching funnel for a two-sided healthcare hiring marketplace. Define product vision, roadmaps, priorities, user journeys, KPIs, experiments, and feature concepts while balancing candidate and employer needs. Collaborate with engineering, data, and stakeholders to deliver complex workflows, evaluate technical trade-offs, and improve measurable business outcomes. The role requires marketplace product experience, strong analytics and experimentation skills, technical fluency, and excellent German and English communication.

Own full-stack features from concept through production across frontend, backend, data, and infrastructure. Build TypeScript software, testing guardrails, CI/CD, observability, and secure AI-assisted development workflows. Use and critically review AI coding agents, improve deployment speed, instrument releases, conduct code reviews, mentor colleagues, and collaborate with product, QA, and data teams.