Finance Systems Analyst

About Kerry

Kerry is the world's leading taste and nutrition company for the food, beverage and pharmaceutical industries. Every day we partner with customers to create healthier, tastier and more sustainable products that are consumed by billions of people across the world. Our vision is to be our customers' most valued partner, creating a world of sustainable nutrition. A career with Kerry offers you an opportunity to shape the future of food while providing you opportunities to explore and grow in a truly global environment.

Key responsibilities

- Responsible for the maintenance of applicable finance systems (e.g. Intercompany Matching System) and develop custom reports to meet the requirements of finance management and staff.

- Responsible for the set-up of standard master data relating to financial systems including new users, new sites, new relationships and maintenance of tables interfacing between financial systems and Kerry’s key ERP system, SAP.

- Responsible for problem solving where failures arise between financial system and SAP including management of tickets

- Manage the monthly and year end roll over tasks of financial systems

- Configure system settings and options, as well as create specifications for systems to meet financial requirements.

- Provide expert knowledge to users in the areas of automated finance systems.

- Support cross-functional linked teams in addressing finance systems issues.

- Assist the Operations unit in the development and use of applicable finance system applications.

- Utilize automated systems in the analysis of financial problems.

Qualifications and skills

•  Bachelor’s degree in accounting, finance or equivalent, with 3+ years of experience in a data-driven role.

•  Strong analytical and communication skills.

•  Advanced skills in Microsoft Excel and PowerQuery

•  Demonstrated experience in designing and building dashboards for a broad audience in Power BI, added advantage.

•  Proficient in data analytics – Analyzing voluminous data, designing and optimizing data processing pipelines, and aggregating multiple data sources.