Data Analyst

Job Description

Purpose The Finance Data Analyst is responsible for enabling data-driven decision-making and supporting Finance's digital transformation through data analytics, automation and modern digital technologies. The role partners with Finance, Technology and business stakeholders to develop scalable reporting and analytical solutions, implement automation, improve data quality and governance, and deliver actionable insights that enhance operational efficiency, business performance and Finance capabilities.

Responsibilities Data Analytics & Business Intelligence Develop and maintain data extraction, transformation and validation processes to support scalable reporting, analytics and automation solutions.

• Develop SQL queries, reusable datasets and data models to support reporting, automation and business intelligence.
• Transform enterprise data into meaningful business insights that support strategic and operational decision making.
• Design, develop and maintain interactive dashboards, visualisations and self-service reporting solutions using enterprise Business Intelligence platforms.
• Apply descriptive, diagnostic and predictive analytics to identify business trends, risks and opportunities for continuous improvement.

Automation & Digital Technologies

• Identify opportunities to simplify, standardise and automate Finance processes through workflow automation, digital technologies and AI-enabled solutions.
• Design, develop, implement and maintain automation solutions that improve productivity, strengthen controls, reduce manual effort and enhance operational efficiency.
• Develop reusable automation workflows, scripts and digital solutions to improve Finance operations and reporting.
• Evaluate and leverage emerging technologies, including Artificial Intelligence (AI), to enhance Finance reporting, analytics, forecasting and decision support, ensuring appropriate governance, quality and compliance.
• Monitor, optimise and continuously enhance automation solutions to ensure reliability, scalability and business value.

Finance Transformation

• Support Finance transformation initiatives involving ERP, enterprise data platforms, automation, AI and process redesign.
• Partner with Finance, Technology and business stakeholders to design and implement technology enabled solutions that improve Finance processes and business outcomes.
• Review existing Finance processes and recommend innovative, technology-enabled improvements to enhance efficiency, controls and user experience.

Qualifications

• Bachelor's Degree in Business Analytics, Information Systems, Computer Science, Statistics or a related discipline.
• 3–5 years' experience in Finance Analytics, Business Intelligence, Data Analytics, Finance Transformation, Automation or Digital Transformation.
• Experience working with Finance, ERP or enterprise systems is preferred.
• Experience designing and implementing automation or digital solutions is an advantage.

Technical Competencies

• SQL, including data querying, extraction, transformation and validation.
• Data modelling and data preparation.
• Business Intelligence and data visualisation (e.g. Tableau, Power BI, IBM Cognos Analytics or equivalent).
• Cloud data platforms and enterprise data warehouses (e.g. Snowflake or equivalent).
• Workflow automation and low-code automation platforms
• Robotic Process Automation (RPA) platforms (e.g. UiPath)
• Programming or scripting languages (e.g. Python).
• Artificial Intelligence (AI) and Generative AI tools.
• API integration and system connectivity concepts.

Core Competencies

• Strong analytical and problem-solving skills with the ability to translate data into actionable business insights and automation solutions.
• Good understanding of Finance processes and business operations.
• Strong process improvement and automation mindset with the ability to identify opportunities to simplify and optimise Finance operations.
• Strong stakeholder management, communication and presentation skills.
• Ability to translate business requirements into scalable technology enabled solutions.
• Strong attention to detail and commitment to data quality, governance and operational excellence.
• Self-motivated, innovative and able to manage multiple priorities in a dynamic environment.
• Curious, adaptable and committed to continuous learning in emerging technologies.