Responsibilities

• Take on technical responsibility for groundbreaking customer projects.
• Understand not only the technology, but also the business context behind it.
• Think strategically, communicate clearly and enjoy working in a team.
•  Analyze challenges, recognize potential and develop data-driven concepts that deliver real added value.
• Advise customers on technologies, architectures and implementation options - clearly, understandably and at eye level.
• Manage the implementation in the team and ensure transparency for all parties involved.

Qualifications

• 7+ years of experience in architecting, implementing, and communicating end-to-end data solutions (e.g., data pipelines, AI/ML systems) across industries. Includes translating business needs into technical architectures.
• 5+ years of client-facing consulting experience, advising enterprises on data strategy, technology adoption, and implementation roadmaps. Proven ability to align technical solutions with business goals.
• 7+ years of hands-on expertise in data engineering (ETL/ELT, Apache Spark, Kafka) and designing scalable data warehouses (e.g., Snowflake, Redshift).
• 7+ years of experience building cloud-native solutions (AWS/Azure/GCP) with DevOps practices (CI/CD, Docker, Kubernetes) and infrastructure-as-code (Terraform).
• 7+ years of proficiency in Python or Java/Scala for developing data applications, APIs, or automation tools. Familiarity with frameworks like TensorFlow or PyTorch
• 7+ years of experience integrating data science models (MLOps, NLP, analytics) into production systems, with a focus on delivering actionable business insights.

Additional Requirements:

• Fluent in German (C1+) and English for client communication.
• Willingness to travel (10–15%) for on-site client engagements.