Senior Data & AI Engineer

Your role in the team

• Design and development of modern data platforms (Lakehouse, Mesh)
• Technical leadership & mentoring of junior engineers
• Development of ETL/ELT pipelines with Dataflow, Dataproc & dbt
• Code reviews, architecture assessments & documentation
• Modeling of BigQuery data models (Star, Snowflake)
• Requirements analysis with Product Owners & Stakeholders
• Deployment & Monitoring of ML models via Vertex AI
• Cost Optimization & FinOps Consulting in the GCP Environment
• Infrastructure Automation with Terraform & Cloud Build
• Incident Management & On-Call Readiness (rotating)
• Implementation of data governance and data protection concepts
• Evaluation of new GCP services & Proof-of-Concepts
• Feature Engineering & MLOps Pipeline Design
• Co-creation of the Data Platform Roadmap

What we offer

• The opportunity to shape the technological future of an established specialist publisher
• Modern work environment with high flexibility and up to 80% remote work possible
• Personal development in a highly digitization-focused environment
• A competitive compensation package with a permanent employment contract, company pension scheme, and additional fringe benefits in a forward-looking media company.
• Structured onboarding, a buddy system, and a coordinated induction to help you quickly get to know your tasks.
• A modern workplace concept with up-to-date equipment at the Frankfurt location and the option for mobile working.
• Professional and personal development opportunities tailored to your individual needs.

Technologies and skills

• Google BigQuery
• Vertex AI
• Google Cloud Platform
• Terraform

Our expectations:

Qualifications

• Technical leadership competence: ability to lead teams and make technical decisions
• Communication skills: Conveying complex technical issues to non-technical stakeholders
• Analytical thinking and structured problem-solving skills
• Own responsibility and proactive working style in agile environments (Scrum/Kanban)
• Willingness to continuous learning in the rapidly evolving AI/ML environment
• Ability to work in a team and willingness to collaborate in cross-functional teams
• Critical thinking: Questioning requirements and proposing alternative solutions.

Experience

• Relevant experience in Data Engineering, ML Engineering, or Cloud Engineering, as well as hands-on experience with Google Cloud Platform.
• Experience with enterprise projects (>50 GB/day data volume, 5+ team size)