• Conceptual Data Modeling
• Logical Data Modeling
• Physical Data Modeling
• Dimensional Modeling
• Star Schema
• Snowflake Schema
• ER Modeling
• ER/Studio
• Erwin
• Oracle
• SQL Server
• PostgreSQL
• Snowflake
• Amazon Redshift
• MongoDB
• SQL
• PL/SQL
• T-SQL
• Python
• Shell Scripting
• Data Warehousing
• Kimball
• Inmon
• ETL
• Informatica
• AWS
• S3
• Glue
• Databricks
• dbt
• Alation
• Metadata Management
• Data Governance
• Data Lineage
• Performance Tuning
• JIRA
• Confluence

Join Barclays as a Data Modeler / Architect responsible for designing, implementing, and maintaining conceptual, logical, and physical data models that meet both business and technology requirements. You will support the delivery of Location Strategy projects to plan, budget, and agreed quality and governance standards.

Your responsibilities include analyzing and documenting business requirements to translate them into data models aligned with organizational goals, developing and maintaining data dictionaries and glossaries, and monitoring data usage patterns to identify optimization opportunities. You will work with star and snowflake schemas, normalization/denormalization techniques, and entity-relationship modeling.

You will collaborate closely with business analysts, product managers, stakeholders, engineering, and compliance teams to translate business requirements into robust data models. The role also involves performance optimization through indexing strategies, partitioning, clustering, and query tuning for large datasets, as well as designing data quality controls for accuracy, completeness, and consistency.

Experience with investment banking data concepts such as deals, CRM, instruments (equities, bonds), reference data, and market data vendors (Bloomberg, FactSet, Refinitiv, Dealogic) is highly valued. Familiarity with cloud platforms (AWS including S3, Redshift, Glue), data governance and lineage tools, ETL tools like Informatica, and modern platforms such as Snowflake, Databricks, and dbt is expected.