Lead Data Platform Architect
- ML Operationalization: You understand how to successfully develop data and machine learning projects from the prototype phase into production and implement such concepts as traceability, transparency, scalability and measurability within a demanding project and technology environment
- Architecture, Implementation: As a data platform architect, you will lay the foundations for state-of-the-art solutions of demanding machine learning projects. Subsequently, you will outline these to the relevant stakeholders to inspire them and secure their buy-in
- Methodology, Concepts: You have a sound understanding of modern data platform architectures, data security and bring along the right Data Governance and DevOps mindsets
- Concepts: In your work, you rely on your strong methodology and concept-driven approach to design an optimal and sustainable solution for the client. You contribute the knowledge gained in your mandates to further develop the methods and procedures
- Cloud: You feel "at home" in the cloud and on-premises and you're able to design and implement the optimal customer solutions with GCP, AWS and Azure
- Data Engineering: Your deep Data Engineering know-how allows you to successfully lead your team in our state-of-the-art/top-noth projects with the right methodologies, optimal data structures, data processing pipelines and data management strategies
- Consulting, Training: You perceive Data Science and Machine Learning as a tool to master the challenges of the Digital Transformation of our clients and help them to understand their full potential
- Solution & Offer development: You are an important exponent for data platforms, are active in the development of Zühlke services, position our offer on the market (pre-sales) and prepare offers. In addition, you are familiar with market trends and always keep an eye on current developments
- Thought Leadership: take on a challenge of becoming a thought leader in the field of data platforms and continue to strategically advance the topic internally and externally. Share your knowledge with colleagues, train customers and help develop young talents
- Sound knowledge of different aspects of Data Science and Machine Learning solutions and a deep understanding of their possibilities and limitations
- You're passionate about sustainable software architecture in the area of data platforms and have a proven track record of managing and working on technical projects
- Thanks to your self-confidence in communication with customers and strong drive and passion, you're striving to take on responsibility in projects and in the further development of our data and machine learning capability. Excellent communication skills in German and English are a prerequisite
- Your architecture decisions are significantly influenced by non-functional requirements such as availability, flexibility, stability, maintainability and security, combined with economic considerations. You know what concrete effects your architecture decisions have on the code level
- You have a technical university degree (ETH, Uni) in Computer Science, Mathematics or in a comparable field; PhD in Machine Learning would be a big plus
- Technologies: Be it Apache Airflow, Apache Beam, Kubernetes, Docker, or relational, column-based or NoSQL databases, stream or batch processing, Python, SQL or Java - you are the technology polyglot in the field of Big Data
- Unique culture - we communicate openly with each other, assess ourselves honestly and enjoy working in a team.
- Further development – we invest 10% of our turnover in the development of our employees. We help you grow through continuous, high-quality training.
- Knowledge exchange - we have an interdisciplinary approach, culture of knowledge sharing and learning from each other.
- International topic groups – we exchange experience, knowledge and support each other in our further development within our internal communities (such as Data Platforms, AI & Data Science).
- Great workplace – we offer a culture of trust, encourage you to think outside the box and to share your ideas.