Data Analyst at Rainforest Alliance

At Rainforest Alliance, we believe in the value of data. The Data Management and Intelligence department is paving the way for enabling data-driven decisions by focusing on the delivery of scalable data products, supporting internal decision-making, unlocking the value of data, and creating a solid data foundation on which we can continue to build our data offering.

We are looking for a talented and motivated Data Analyst to join our team and contribute to the development of data-as-a-product solutions. In this role, you will be responsible for creating compelling dashboards and reports, designing reliable data models, and analyzing complex datasets to uncover insights that drive business strategies. You will collaborate with a variety of internal and external stakeholders to understand their data needs, ensuring that the data products meet those requirements and deliver real value.

This position offers an exciting opportunity to contribute to impactful projects and grow in a collaborative, data-driven environment.

• Data Visualization & Reporting: Create compelling and easy-to-understand dashboards, reports, and visualizations using BI tools like Tableau or Power BI to effectively communicate insights to stakeholders.
• Data Modelling: Design and build scalable and reliable data models. Collaborate with the Data Engineering team to meet data requirements and ensure optimal model performance. Leverage best practices to deliver self-service solutions while maintaining flexibility for future enhancements.
• Collaboration & Stakeholder Engagement: Work closely with internal and external stakeholders to understand their needs, gather data requirements, and provide actionable insights that address business challenges. Collaborate with Data Engineering, Architecture, GIS, and Product teams to ensure analytics efforts align with the organization's broader data strategies.
• Data Analysis & Insights: Analyse large and complex datasets to uncover trends, patterns, and insights that inform business strategies and operations.
• Ensure data quality by proactively identifying, analysing, and addressing inconsistencies, anomalies, or inaccuracies within datasets. Collaborate with Data Engineering and business teams to investigate root causes.
• Continuous Learning & Improvement: Stay updated on the latest tools, techniques, and trends in data analysis. Apply innovative methods to enhance the effectiveness and efficiency of analytics initiatives.
• Communication: Effectively present analytical findings to diverse audiences through presentations, workshops, and training sessions. Support teams in building data literacy and understanding analytics tools and insights. Regularly deliver presentations to non-technical audiences, both within and outside the organisation.

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