Software and Data Tester - Finance Transformation Programme

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.

My Role:

The Data Analyst will help shape and validate the finance data needed to support a major transformation programme aligned to Workday Financials. The role sits within the data stream and focuses on data ingestion, mapping, reconciliation, validation, and reporting datasets. It does not include direct Workday configuration or build. This is an opportunity for an analytically strong candidate to work across finance and technology teams, ensuring data moving through finance systems is accurate, traceable, and ready for reporting and audit.

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.