What you will do
Analyzing the existing data landscape (data warehouse, BI, integrations, data models) and mapping dependencies, risks, and opportunities for improvement. Translating business objectives into a scalable, secure, and high-performing target architecture.Designing and validating conceptual, logical, and physical data models.Developing the data integration strategy, encompassing ETL/ELT, batch processing, and real-time streaming. Formulating a migration roadmap from legacy systems to modern cloud and lakehouse platforms. Evaluating and selecting tools and platforms for data storage, integration, data quality, cataloging, and analytics. Structuring data governance framework, including data quality, metadata management, data lineage, master data management (MDM), and access control. Ensuring robust security, privacy, and GDPR compliance across all architectural decisions. Preparing data infrastructure for AI applications in close collaboration with BI and AI specialists. Mentoring data engineers and analysts, while driving the adoption of standards and industry best practices.