At Antares, our success starts with our people. We’re a collaborative and an inclusive organisation where every voice is valued, and every individual can grow and thrive.
We combine deep expertise with a supportive culture to deliver outstanding results for our clients and a fulfilling experience for our colleagues.
Whatever stage of your career you'll find a place to belong, contribute, develop and we’d love to hear from you.
Key Aspects of the role:
- Define required finance data attributes, field definitions, and dataset requirements to support reporting, reconciliations, and downstream journal creation.
- Analyse and document source-to-target mappings so that finance data is aligned to agreed structures, Workday-required values, and reporting needs.
- Support data ingestion activities by validating incoming datasets, checking completeness, and confirming that records are fit for downstream processing.
- Design and execute reconciliation logic across source data, outputs, Prism datasets, Accounting Centre outputs, and reporting results.
- Identify data quality issues, investigate root causes, and work with business and technical teams to improve data accuracy and control effectiveness.
- Define point-in-time and snapshot requirements so period reporting remains traceable, explainable, and auditable over time.
- Prepare analytics-ready datasets and report specifications for Workday and approved downstream reporting tools.
- Produce validation evidence to support SIT, UAT, production readiness, and ongoing finance control requirements.
- Look at historical data to check its fit for the rules in Financial & Actuarial (F&A) module
- Analyse and document finance data structures and reporting requirements, maintaining robust data lineage and controls.
Accountabilities and KPIs
- Create Source-to-target mapping documents and field-level data definitions for the finance data stream.
- KPI: Source-to-target mappings and data definitions are complete, accurate, and approved, enabling successful downstream processing, minimal defects, and full audit traceability.
- Create data contracts and dataset specifications aligned to Actuarial, Ceded, F&A, Prism and reporting requirements
- KPI: Contracts and dataset specifications are defined, agreed, and maintained, ensuring alignment with business requirements and no critical post-go-live issues.
- Create data quality rules, validation outputs, and issue logs showing how completeness, validity, and consistency are assessed.
- KPI: Controls are established and effective, with high data accuracy and timely resolution of issues in line with agreed standards.
- Create reconciliation and validation requirements covering Source to F&A, F&A to Ceded, Ceded to F&A, F&A to Actuarial, Actuarial to F&A, F&A to Prism and report to general ledger checks.
- KPI: Reconciliation processes are defined and operating effectively, with minimal variances and timely investigation and resolution of exceptions.
- Develop snapshot and history-tracking requirements to support point-in-time reporting and audit traceability
- KPI: Data retention and history tracking are in place, enabling reliable point-in-time reporting and compliance with audit requirements.
- Assist with creating test scripts, evidence and production readiness artefacts supporting SIT, UAT, and business sign-off to “Go Live”.
- KPI: Testing artefacts are delivered to a high standard, supporting successful test outcomes and readiness for deployment with no data-related blockers.
- Takes responsibility for their own and colleagues’ Health & Safety at all times
- To ensure customers are treated fairly at all times, in accordance with the Conduct Risk Policy and other relevant policies and procedures.
- To be aware and adhere to all obligations under GDPR, ensuring that the business complies with these requirements.
Knowledge And Qualifications
§ Proven experience in data analysis, finance data transformation, reconciliation, or analytics delivery within finance, ERP, or enterprise reporting programmes.
§ Strong capability in data mapping, validation, reconciliation, and audit traceability across multi-system data environments.
§ Good understanding of finance data structures, controls, reporting requirements, and the importance of data lineage in regulated reporting environments.
§ Practical analytical skills using SQL and structured data analysis techniques; experience with reporting datasets and BI concepts.
§ Ability to work confidently with both business and technical stakeholders and translate requirements into robust, usable data outputs.
§ Exposure to Workday Financials concepts, including an understanding of how Prism Analytics and Accounting Centre support reporting and journals, is advantageous
Experience with large scale Finance transformation projects, London Market insurance or regulated financial services is desirable
Skills and Demonstrated Experience
§ Experience with Workday Prism Analytics or similar data preparation and reporting platforms.
§ Experience with subledger, journals or accounting-hub style solutions in high-volume finance environments.
§ Familiarity with Power BI, Qlik, Excel-based reporting packs, or other enterprise reporting tools used alongside ERP platforms.
§ Practical analytical skills using SQL and structured data analysis techniques
§ Experience in insurance, technical accounting, reinsurance, actuarial, IFRS 17, or other regulated data environments.
§ Exposure to controlled testing approaches, including SIT/UAT evidence preparation and defect investigation.
Ability to work confidently with both business and technical stakeholders and translate requirements into robust, usable data outputs.