Defining and owning the data platform strategy and architecture for digital service solutions, covering cloud-native data platforms, data lakes/lakehouses, streaming and batch pipelines, and analytics services.
Establishing architectural principles and standards aligned with modern cloud delivery models, industrial scalability, and long-lifecycle service solutions.
Governing data ingestion and integration patterns from cloud services, enterprise systems, IoT, OT devices, and edge software.
Designing and maintaining data models, schemas, and integration patterns that ensure consistent, reusable, and high-quality data across solutions.
Establishing and operating data governance frameworks, including data quality, lineage, traceability, ownership, and lifecycle management.
Ensuring compliance with cybersecurity, regulatory, and industrial data handling requirements.
Enabling advanced analytics, AI/ML, and digital twin use cases through appropriate data platform capabilities, pipelines, and analytics services.
Guiding implementation of robust, scalable data pipelines and storage solutions in collaboration with development, platform, DevOps, AI, cybersecurity, and IT teams.

University degree (Bachelor’s or Master’s) in Data Science, Computer Science, Engineering, or a related technical field.
Proven experience in designing, implementing, or governing cloud-based data platforms in complex digital or industrial environments.
Strong understanding of data modeling, data pipelines, and data lifecycle management.
Experience with data ingestion from IoT, OT, and enterprise systems.
Solid knowledge of data governance, data quality management, and traceability concepts.
Experience working in agile, hybrid, or scaled development environments.
Strong communication skills and ability to collaborate across global, cross-functional teams.

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Lead Data Platform Architect

Key skills