Senior Data Architect

Tools & Technologies Must-Have

• Google Cloud Platform (GCP) — BigQuery (Data Lakehouse architecture, performance, scalability)
• Data architecture & modeling (conceptual, logical, physical; domain-driven data modeling)
• ETL/ELT tools and integration patterns (batch, API-based, CDC)
• Data governance & metadata management concepts (data catalogs, MDM, lineage tools)
• Data quality assessment/profiling methods and tools
• Experience with data architecture in Telecom or similarly complex enterprise environments
• Strong stakeholder engagement, interviewing, and documentation skills (architecture diagrams, inventories, roadmaps) Good-to-Have
• Experience with GCP ecosystem tools beyond BigQuery: Dataflow, Data Fusion, Dataplex, Vertex AI, Cloud Composer
• Exposure to AI/ML data enablement and data ontology design for AI use cases
• Knowledge of GDPR and telecom-specific regulatory/compliance frameworks
• Experience with legacy on-prem data warehouse/lake platforms and hybrid cloud migration
• Familiarity with data governance/compliance frameworks (DAMA-DMBOK, DCAM)
• Prior consulting/advisory experience delivering data strategy assessments (vs. pure implementation)
• Familiarity with telecom OSS/BSS systems and network data domains