Switzerland állások Németországban (it programozás, fejlesztés)

As a Senior Solution Engineer, you will play a key role in implementing SAP solutions for warehousing and transportation transformation projects, with a particular focus on SAP EWM. Your responsibilities include migrating existing warehouse management solutions -starting in Switzerland- and...

• Deep Discovery: Using user-centred and data-informed design to understand exactly what our patients need to succeed.
• Collaborative Innovation: Partnering closely with stakeholders to align on a product vision that is both impactful and technically feasible.

• Translate business goals into innovative, scalable solution strategies that improve customer value.
• Independently deliver foundational cross-solution strategies.
• Provide mentorship on metadata standards, governance models, approval flows, DAM structure and authoring practices

• Define and deliver a compelling product vision for long-term retention across our app platform.
• Drive the development of platform capabilities from content delivery and in-app messaging to user journeys and community features.

• Plan and conduct user interviews, surveys, and usability tests to gather actionable insights
• Lead end-to-end product design
• Design user flows, wireframes, and high-fidelity mockups that solve real user problems
• Lead and participate in weekly design critiques to continuously improve design quality

• Lead and grow a team of product designers across 3-4 squads, fostering collaboration and high design quality.
• Shape the vision for Oviva's Behaviour Change Engine - our core habit-building system - to deliver better patient outcomes.

• Align customer needs and vision with SAP BTP solutions early in the sales cycle
• Showcasing SAP solutions addressing customers' specific business requirements
• Mapping product capabilities to business requirements
• Responding to inquiries from customers within set deadlines, focusing on customer success

• Develop, test, deploy, and monitor scalable filter pipelines and transformation processes that extract relevant metrics and features from billions of events.
• Data management in a Data Lake.
• Collaborate with data scientists and software developers to optimize and scale high-performance ML models.