data architect.

Domain Expertise: In-depth knowledge and profound experience in data architecture, data governance, and data strategy development.
Project Experience: Active, end-to-end involvement in Data Warehouse projects and the transition from traditional to modern data structures.
Data Modeling Mastery: Expertise in designing conceptual, logical, and physical data models for both structured (Relational/ERP) and unstructured (NoSQL/Lakehouse) datasets.
Modern Data Stack Strategy: Proficiency in designing hybrid-cloud data platforms (Snowflake, Databricks, or cloud-native AWS/Azure/GCP big data services) and ETL/ELT orchestration.
Data Governance Quality: Ability to implement enterprise-grade data governance frameworks (Data Cataloging, Lineage, Master Data Management) to ensure compliance with KVKK, GDPR, and holding-level audit requirements.
Security Privacy: Expert-level knowledge in data security, data privacy, and the technical integration of KVKK and GDPR regulations into the infrastructure.
Communication Technical Acumen: Possessing the high technical proficiency required to debate solutions with technical authorities, combined with the strong communication skills needed to guide and influence business units.
Leadership: A visionary with strong leadership qualities who doesn't just set the rules, but actively persuades stakeholders to ensure their successful implementation.
Continuous Learning: Always open to learning new technologies, tools, and architectural approaches.
Industry Experience: Preferably experienced in working with complex data structures within the Manufacturing (sector experience is a significant plus), Retail, or Telecommunications industries.
Education: Bachelor’s degree from an Engineering faculty.
Language Skills: Advanced level of both spoken and written English.