Data Modeller
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 Lake house 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.
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