ERP Data

6 months ago

Singapur, Singapore Prudential plc Full time

Prudential’s purpose is to be partners for every life and protectors for every future. Our purpose encourages everything we do by creating a culture in which diversity is celebrated and inclusion assured, for our people, customers, and partners. We provide a platform for our people to do their best work and make an impact to the business, and we support our people’s career ambitions. We pledge to make Prudential a place where you can Connect, Grow, and Succeed.

The ERP Data & System Analyst is responsible for leading the design, implementation, and definition of the data & solution architecture for the Oracle Fusion Financials ERP (inclusive of AHCS) implementation.
This role collaborates closely with cross-geo teams (Pilot entity and wave 1 entities), cross-functional teams (& other FFP workstreams) and cross-systems teams (source & consuming systems teams from both local business entities and group office) to ensure the integrity, security, and performance of Prudential’s E2E closing throughout the system lifecycle.

Role and Responsibilities

1. Lead Data & Solution Architecture Design:

Design and develop a robust and scalable (across multi-entities in multi-geo/multi-TRM setting) data architecture for the Oracle Fusion Financials ERP implementation. Support in defining data architecture, data flows, and E2E data integration points across various financial modules (GL/AP/FA/…), IFRS 17 subledger solution, Oracle AHCS, OneStream, Smartstream TLM, etc… Collaborate with the Solution Architect and other stakeholders (data workstream teams) to ensure data architecture alignment with the overall ERP system architecture. Lead and review technical design documents, including data dictionaries, data flow diagrams and low level design of target solution

2. Lead technical design on NFRs with Oracle & other systems: Performance, Compliance and Security management

Ensure compliance of the data architecture with relevant financial regulations, accounting standards, and data privacy requirements Design and implement data security controls, such as data encryption, access controls, and audit trails, across the Oracle Fusion Financials ERP ecosystem Collaborate with the security and compliance teams to ensure adherence to industry standards and regulatory requirements across SEA for insurance industry.

3. Support E2E QA (with focus on SIT), Data Migration and Integration:

Support in definition of test plan, migration plan and execute data migration activities from legacy systems to Oracle Fusion Financials ERP Help in design and implement test cases, data migration strategies, considering data mapping, data transformations, and data validation requirements. Collaborate with the integration specialists to ensure seamless data flow and integration between Oracle Fusion Financials modules and other enterprise systems. Develop and maintain data integration specifications and documentation.

Qualifications

Bachelor's or Master's degree in Computer Science, Information Technology, or a related field 10+ years of experience in designing and implementing data architectures for complex financial systems, preferably in the Oracle ecosystem Experience with data migration, data quality management, and data governance frameworks Excellent problem-solving and analytical skills Strong communication and leadership abilities Ability to work collaboratively in a fast-paced, multi-stakeholder environment

Mandatory skills

Strong expertise in Oracle Fusion Financials ERP modules and their underlying data structures Experience with data architecture, data engineering and integration patterns in Financial Services (with Insurance as preferred). Familiarity with financial accounting concepts and processes (ideally with IFRS 17 exposure)

Preferred skills

Technology delivery project management experience, especially legacy systems migration Experience with DevOps, CI/CD practices, master data management and data governance In-depth knowledge of Oracle Financials data structure and data integration techniques

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