Public summary
This role involves working directly with customers to design, build, and productionize data and AI solutions using a unified data platform. The position includes leading architecture decisions, implementing end-to-end systems involving data engineering, AI, and application development, and collaborating cross-functionally to align technical solutions with business needs. Candidates should have extensive experience in data engineering, cloud ecosystems, distributed computing, and AI/ML technologies, along with strong customer engagement and project delivery skills.
Location and work setup
- Location
- Berlin, Munich
- Remote status
- Hybrid
- German requirement signal
- No German Required Detected
- Detected job language
- English
Responsibilities
Lead customer technical projects to deliver production-grade data and AI systems, including architecture design and implementation. Guide strategic clients through transformational big data initiatives and empower them on architectural best practices. Collaborate with internal engineering, support, and project teams to ensure successful delivery and resolution of technical challenges. Embed with customer teams to deeply understand their challenges and deliver impactful solutions. Contribute reusable frameworks and best practices to scale impact across engagements.
Qualifications
6+ years experience in data engineering, data platform analytics, or software engineering. Proficiency in coding with Python, Scala, JavaScript/TypeScript, and modern frameworks. Expertise in at least one major cloud ecosystem (AWS, Azure, or GCP) and working knowledge of others. Deep understanding of distributed computing with Apache Spark and familiarity with CI/CD pipelines for production. Knowledge of MLOps, AI/ML model integration, and API usage. Strong project management and technical communication skills. Experience working with enterprise clients and handling multi-stakeholder environments. Willingness to travel approximately 20%.