Senior Data Modeller — Asset Management Finance

PwC; Makati; Vor Ort; PHP 850.000 - 1.200.000; Vollzeit

Zusammenfassung

PwC Philippines is seeking a Data Modeller with strong experience in Asset Management to join our advisory data product team. You will help design a finance data mart and support reporting for Funds under Management and Revenue Allocation, collaborating with finance and technology stakeholders.

The role requires deep knowledge of finance operations, data warehousing concepts, and experience with cloud-based platforms such as MS Azure and Databricks.

Qualifikationen

• Proven experience as a Data Modeller within Asset Management.
• In-depth knowledge of Funds under Management reporting and Revenue Allocation methodologies.
• Experience with data modelling tools and source-to-target mapping, including data profiling and transformation logic.

Aufgaben

• Data Modelling: design and develop robust data models for finance reporting (FUM and Revenue Allocation).
• Source-to-Target Mapping: analyse source systems and define mappings to the target data mart.
• Collaboration: work with finance stakeholders and development team to translate requirements into data structures.
• Documentation: prepare docs for data models, mappings, and data flows.
• Quality Assurance: support data validation and reconciliation for accurate reporting.
• Continuous Improvement: identify opportunities to optimise data models and processes.

Kenntnisse

Data-driven modeling

Data modeling techniques

Data modeling tools

Microsoft Azure Databricks

Ausbildung

Bachelor's degree in Finance, Computer Science, Information Systems, or related field

Jobbeschreibung

PwC Philippines is seeking a Data Modeller with strong experience in Asset Management to join our advisory data product team. You will help design a finance data mart and support reporting for Funds under Management and Revenue Allocation, collaborating with finance and technology stakeholders.

The role requires deep knowledge of finance operations, data warehousing concepts, and experience with cloud-based platforms such as MS Azure and Databricks.