Data platform engineer állások, munkák

• Collaborate with all departments to identify, document, and technically implement high-impact AI use cases across the our organization
• Design and deliver onboarding, workshops, and hands-on training sessions tailored to various teams and roles

implement and productionise ML-based services on our AI- and big-data-platform Databricks, using Python, SQL and Linux....

• Design and implement unified data platform architecture (data lake, data warehouse, streaming)
• Build scalable data ingestion pipelines for IoT sensors, transaction data, and external APIs
• Implement real-time data processing systems for operational decision-making

To deliver high-quality, user-focused frontend experiences, you build complex UI features in React & Next.js, develop component-based UI systems and optimize UX together with our Product Managers and Designers....

• Collaborate with cross-functional teams to define data requirements and ensure data quality
• Support the data engineering team in reconciling data between the new and the legacy systems
• Participate in monitoring, troubleshooting, and resolving data processing issues

• You gather and analyze user and system requirements to define clear product needs.
• You document detailed and actionable specifications that guide development teams.
• You facilitate communication and collaboration between cross-functional teams to align technical solutions with stakeholder expectations.

• You gather and analyze user and system requirements to define clear product needs.
• You document detailed and actionable specifications that guide development teams.
• You facilitate communication and collaboration between cross-functional teams to align technical solutions with stakeholder expectations.

• Design and lead development of AI products for business-specific use cases.
• Mentor and guide the software engineering team, setting clear technical directions and providing architectural oversight.

• Design and implement security measures for systems built on Microsoft technologies, including Windows Server, Azure, and Microsoft 365
• Configure and manage Microsoft security tools such as Defender for Endpoint, Defender for Identity, and Defender for Cloud

• Deliver creative customer facing features to bring German users on chain.
• Articulate a long term vision for maintaining and scaling our backend systems.

• You will take ownership of our Google Cloud Platform environments and ensure smooth integration between internal and partner data centers.
• You will build and maintain Kubernetes clusters as the foundation of our development and production environments.

• Design and implement mathematical models for valuation of financial instruments (mainly fixed income and derivatives)
• Migrate, maintain and extend our portfolio management/planning tool to meet regulatory and customer requirements

• Design, implement, and optimize data ingestion and transformation pipelines using Azure Databricks, Data Factory, and ADLS
• Apply automation to streamline and scale recurring data engineering tasks across the CDP

Design, implement, and build data and AI solutions adding business value (Service Efficiency, Sales) – linking strongly to IOT data and other proprietary data sources...

• Maintaining existing as well as creating new Linux applications on the unmanned aircraft.
• Designing and coordinating interfaces between teams, documenting the architecture and design decisions.

• Expand, develop, and maintain infrastructure and development pipelines for our Global Data Platform
• Increase automation in our cloud-based development and production environments
• Administer our cloud-native analytical database system Snowflake

Develop and drive the implementation of Cloud Data Security strategy in alignment with the Product Manager, Tech Lead, and Engineering Manager....

• Oversee and maintain Linux environments across global data centers, ensuring performance, security, and reliability.
• Design, implement, and manage Kubernetes clusters to support scalable and resilient services.

• Design secure architectures for IoT platforms, devices, and cloud-based services
• Embed security principles and controls across the software development lifecycle (SDLC)
• Define and guide secure coding standards, perform code reviews, and ensure compliance with company policies

• Design, develop, and implement platform solutions that enhance the reliability, security, and scalability of the AI Platform infrastructure.
• Provide technical leadership in cloud infrastructure, networking, CI/CD, and security for AI and MLOps workloads.