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take responsibility as Tech Lead Search for the technical quality and architecture of our product retrieval and embedding capabilities based on OpenSearch....

• Design and build backend services in that handle high-throughput, low-latency messaging traffic
• Work on core infrastructure: message queues, delivery guarantees, connection handling, and storage layers
• Debug and optimize systems under real production load, not just in benchmarks

• You work on tasks together with your peers and find your way around our codebase and tools.
• You're getting to know the team and the team.
• You're getting familiar with energy specific wording and processes.
• You actively use our AI-first setup.

• Your responsibility: From day one, you'll own your stories and take end-to-end responsibility for your tasks.
• Your team: You'll work in a small team of no more than five full-stack engineers. Like this, our teams are more efficient and can move fast.

• Develop and specify cryptographic communication protocols
• Design cryptographic systems, such as key management and multi-device synchronization
• Lead Threema's migration to quantum-safe cryptography, together with the cryptography researchers at IBM Research

• Design new protocol features and extensions, such as multi-device sync, group messaging and calls, and write the specifications for them.
• Implement protocol logic in and review implementations across our Android, iOS, desktop and web clients.

• Design, develop, and maintain enterprise-wide data models for analytical and reporting purposes.
• Develop and maintain data integration and transformation processes using SQL, Power Query, and ETL/ELT tools such as Azure Data Factory.

• Surgical microscopes creating surgical augmented reality
• Ultrasound devices creating 3D ultrasound imaging
• Brainlab's own Robotic Arm (Cirq)

• Build and own scalable data pipelines and integration solutions our data warehouse and data platform.
• Integrate and transform data from ERP, CRM, finance, and other enterprise systems.
• Ensure high standards of data quality, reliability, performance, and operational excellence.

Building efficient and scalable ETL/ELT processes to ingest, transform, and load data from various structured and unstructured sources (databases, APIs, streaming platforms) into BigQuery and Cloud Storage...

You understand our platform architecture, existing systems and tech stack (C#/.NET, MongoDB, Docker, Kubernetes, GCP/Azure) deeply enough to independently plan and ship features....

• Whether in the cloud or an on-premises data center, you expertly navigate the world of Big Data, helping our clients make their data business- or operations-ready.
• You access diverse data sources efficiently and reproducibly.
• You design, test, and monitor distributed data processing pipelines.

• Define and further develop the Snowflake platform roadmap in alignment with enterprise data strategy and business priorities
• Establish the platform vision and manage priorities, demand intake and business requirements to maximize business value and support strategic objectives

Trusted Advisor: You guide our clients towards successful solutions to their data challenges. You'll lead design sessions, architecture reviews, proof-of-concept projects and evaluation of new data technologies and vendors....

• Develop, maintain and optimize Python and Linux shell scripts for data extraction, transformation, and loading.
• Build automated pipelines and reusable code modules to support recurring reporting and analytics workloads.
• Ensure accuracy, completeness, and consistency of datasets.

• Develop, maintain and optimize Python and Linux shell scripts for data extraction, transformation, and loading.
• Build automated pipelines and reusable code modules to support recurring reporting and analytics workloads.
• Ensure accuracy, completeness, and consistency of datasets.

Advise business units and senior stakeholders on AI opportunities, strategic priorities, target operating models, and the practical implications of emerging AI technologies...

• Write code that is simple, readable, testable, and maintainable, whether you write it yourself or with the help of AI tools
• Conduct code reviews, give helpful feedback, actively contribute in team discussions and decisions

• Developing multi-scale and multi-modal representation learning methods for scientific imaging data (e. g., SEM, TEM, EBSD).
• Learning representations that are robust to scale changes, modality shifts, and domain differences across instruments and laboratories.

• The data platform end to end: ingestion, storage, and the query paths that keep millions of records fast on screen. You design it, you build it, you run it in production.
• The platform layer, directly with the CTO: infrastructure, deployments, and the path to production for the whole team.