Finance Analytics Engineer
Summary
Builds and maintains data pipelines, dashboards, and automation tools to deliver finance/commercial insights; bridges business needs with technical execution using Excel, SQL, Python, and BI tools.
The Finance Analytics Engineer is responsible for developing and maintaining data solutions that enable accurate, timely, and actionable business insights for Finance and Commercial teams. This role designs and manages data pipelines, maintains critical master data, automates business processes, and develops interactive dashboards to support data-driven decision-making across multiple markets and business functions.
Key Responsibilities
Data Management & Governance
- Maintain and govern business master data to ensure accuracy, consistency, and integrity across systems
- Develop and implement data validation, reconciliation, and quality control processes
- Document data definitions, business rules, and data transformation logic
- Design, develop, and maintain ETL processes to consolidate data from multiple sources
- Automate recurring data processing and reporting workflows
- Develop, maintain, and enhance interactive dashboards and self-service reporting solutions
- Build standardized datasets to support consistent business reporting across markets
Automation & Digital Solutions
- Identify opportunities to automate manual business processes
- Develop automation solutions using Excel, Python, and other technologies to improve operational efficiency
- Support deployment and maintenance of web-based analytics solutions
Business Partnership
- Translate business needs into scalable analytical and reporting solutions
- Provide analytical support for strategic initiatives and ad hoc business requests
Requirements
- Bachelor's degree in Data Science, Data Analytics, Business Analytics, Finance, or a related discipline
- Minimum 3 years of experience in data analytics, business intelligence, data engineering, or reporting automation (FMCG experience will be a plus)
- Good proficiency in Excel (including Power Query), SQL, and Python
- Hands-on experience building dashboards in Power BI, Tableau, or Looker
- Experience deploying a dashboard to a web-based server is an advantage
- Comfortable working with data from multiple sources, including manual/Excel-based inputs and non-standardized formats, in addition to system-generated data (e.g. SAP)
- Excellent attention to detail, with the ability to perform detailed data mapping and validation