Anaplan Business Analyst - Finance Data Analysis

Background

As part of a key transformation initiative, the organization is modernizing its operational model and technology infrastructure to enable consistent performance across its global markets. Central to this effort is the redesign of core processes through innovative data management strategies, ensuring scalability and effective day-to-day operations.

The Anaplan Business Analyst - Finance Data Analysis will be at the forefront of driving improvements in how finance-related data is managed, integrated, and delivered in the management information system. Collaborating with diverse teams across operations, FP&A, IT, and other internal business functions, this role will involve mapping current processes, identifying inefficiencies, and implementing future-forward data management solutions. Proficiency in Anaplan is a key requirement for this role, as the business relies on the platform for financial planning and process optimization.

1. Requirements Gathering & Scoping

   • Collaborate with stakeholders to define project scope, gather business requirements, and establish KPIs for the data lake project and Anaplan-based financial processes.
   • Translate business needs into functional requirements for Anaplan models, ensuring alignment with overall transformation objectives.

2. Anaplan Model Development & Management

   • Design, build, and maintain Anaplan models to support financial planning, forecasting, and reporting processes.
   • Develop and document Anaplan model architecture, including data integrations, calculations, and workflows.

3. Data Source Analysis

   • Investigate and document existing data sources, including their schemas, formats, and data flows from legacy systems to Anaplan and the data lake.

4. Data Extraction & Mapping

   • Define extraction requirements, map legacy data fields to the Anaplan architecture and data lake structure, and ensure data integrity during migration.

5. Legacy System Assessment

   • Analyze legacy applications, identify dependencies on data sources, and plan for decommissioning or migration where applicable, with a focus on Anaplan integration.

6. Solution Design & Documentation

   • Contribute to data lake architecture design and Anaplan model processes, creating clear documentation, including workflows, data models, and process diagrams.

7. Data Quality & Governance

   • Establish data quality rules, ensure compliance with governance standards, and address data accuracy or reliability issues in both the data lake and Anaplan systems.

8. Testing & Validation

   • Define test cases, validate data ingestion accuracy, and support user acceptance testing (UAT) to meet business requirements.
   • Perform end-to-end testing of Anaplan solutions to ensure they meet business needs and are error-free.

9. Stakeholder Collaboration & Reporting

   • Act as a liaison between business and technical teams, provide regular project updates, and deliver insights to support decision-making.
   • Train and support end-users on Anaplan functionality and best practices.

• 2-5+ years of experience in business analysis, primarily within data transformation projects/data analysis, ideally with hands-on experience in Anaplan (design, build, and maintenance).
• Experience will be given to Big 4 consultants who are currently in (Senior) Consultant II/III and are looking to move into an in-house role.
• Experience preparing BRDs end-to-end, both in Agile and Waterfall environments.
• Deep understanding of Anaplan's capabilities and how to leverage them for financial planning, forecasting, and operational process optimization will be a HUGE plus.
• A strong understanding of Insurance operations and the finance domain would be a huge advantage.
• Proven track record in redesigning and optimizing data processes for scalability and governance.
• Experience collaborating with external providers and internal stakeholders, ensuring proper scoping of requirements.
• Strong analytical and communication skills, with the ability to document and present complex processes clearly.
• Familiarity with data governance principles, control frameworks, and ownership models.
• Experience working with global or multinational organizations is preferred.