Data Modeller

Technical Skills Required Mandatory skills • Advanced Conceptual, Logical, and Physical Data Modelling expertise with strong experience using modelling tools such as Erwin or ER/Studio. • Expert-level SQL optimization and PL/SQL programming with extensive experience in Oracle and SQL Server environments. • Strong experience in investment domain data modelling including IBOR, portfolio, trade, position, cashflow, and reference data management. • Hands-on experience with Databricks for large-scale data processing, data harmonization, lineage, and lake-house implementations. • Proficiency in logical and semantic data modelling, source-to-target mapping, metadata management, and data governance using tools such as ER/Studio or Erwin Data Modeler. • Strong expertise in enterprise data governance, automated lineage tracking, and access control frameworks using Databricks Unity-Catalog. • Experience designing ML-ready analytical data models, feature datasets, and data preparation frameworks supporting machine learning workflows. • Strong expertise in dimensional modelling, normalized data modelling, and enterprise analytical data modelling techniques. • Deep experience in query execution plan analysis, indexing strategies, partitioning design, and database performance tuning for large-scale analytical databases. • Hands-on experience designing analytics data platforms on AWS, including large-scale data storage and analytics architectures. • Experience implementing Lakehouse architectures using Databricks with Apache Spark and Delta Lake. • Proven experience building and maintaining enterprise documentation portals using Confluence, including architecture documentation, data dictionaries, and governance standards. • Familiarity with version control systems and collaborative development workflows for enterprise data platforms.