Data Modeler / Architect

Job Overview: As a Data Architect at Client, you will be the primary designer of high-performance data ecosystems that transform raw information into AI-ready assets. This role is focused on building sophisticated, scalable data models and structural blueprints that support advanced analytics, predictive modeling, and the integration of Generative AI. You will work as a strategic technical leader, bridging the gap between complex business requirements and robust engineering execution to drive measurable ROI for our global clients. Key Responsibilities: • Architectural Strategy: Define and lead the end-to-end data architecture strategy, ensuring alignment with long-term business goals and advanced analytics requirements. • Strategic Data Design: Design and implement complex conceptual, logical, and physical data models optimized for high-performance analytics and reporting. • Medallion Architecture: Architect scalable Lakehouse environments using Bronze, Silver, and Gold layer patterns to ensure data quality and lineage. • Governance & Standards: Establish enterprise-wide data standards, including metadata • management, data security protocols, and master data management (MDM). • AI Readiness: Partner with Data Science teams to ensure data architectures are optimized for LLM integration, Vector databases, and RAG pipelines. • Cross-Functional Leadership: Orchestrate collaboration between data engineers, business consultants, and stakeholders to translate business logic into technical blueprints. Technical Expertise: • Professional Experience: Minimum 8+ years in Data Architecture or Senior Data Engineering within an Analytics-heavy environment. • Data Modeling Mastery: Extensive experience in Logical and Physical data modeling techniques, including 3NF, Dimensional Modeling (Star/Snowflake), and Data Vault 2.0. • Reverse Engineering: Proven expertise in Reverse Engineering techniques to document and modernize legacy database schemas into optimized target architectures. • Modeling Stacks: Expert proficiency in industry-standard tools such as ER/Studio, Erwin Data Modeler, or Lucidchart for designing relational and non-relational structures. • Cloud & Big Data: Hands-on experience architecting solutions on Azure (Fabric/Synapse), AWS (Redshift/Glue), or Snowflake, utilizing Delta Lake and Spark-based processing. • Advanced Database Systems: Deep knowledge of SQL (PostgreSQL, SQL Server) and NoSQL systems, along with Vector Databases (Pinecone, Milvus) for AI-driven applications.