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.