Sustainability Data & Reporting Lead

Position Overview:

The Sustainability Data and Reporting Lead is responsible for ensuring the accuracy, integrity, and audit readiness of Dolbys sustainability and greenhouse gas (GHG) data. The role applies technical and analytical skills to GHG emissions accounting to deliver high quality, defensible reporting outputs

Key Responsibilities

• Prepare and maintain Dolbys annual carbon footprint, including Scope 1, Scope 2, and Scope 3.
• Work cross-functionally across the organization to gather data from internal stakeholders.
• Review data for completeness, calculation accuracy, and consistency; investigate variances and data issues and support resolution efforts.
• Maintain clear documentation of data sources, assumptions, and calculations to support internal review and external assurance.
• Leverage AI assisted analysis and automation techniques where appropriate, to streamline data tasks and support validation workflows.
• Assist in the preparation of Dolbys voluntary and mandatory sustainability disclosures, including: the annual Sustainability Report, CDP, NFRD, CSRD, etc.
• Utilize and maintain existing systems (Metrio and Watershed) for reporting of ESG data.
• Prepare ESG data to respond to customer and investor inquiries.

• Bachelors degree in Environmental Science, Sustainability, Environmental Management, or a related field; Masters degree preferred.
• 5–7 years of experience in corporate sustainability reporting, greenhouse gas accounting, or a related data-focused role.
• Hands on experience working with Scope 1, Scope 2, and Scope 3 emissions data.
• Strong Excel skills, including working with formulas, pivots, and large datasets.
• Ability to work independently on defined assignments while seeking guidance as needed for new or complex issues.
• Willingness to participate in meetings that take place in Pacific Time Zone (once a week on average).

• Experience with energy management.
• Exposure to third party assurance or verification processes for sustainability data.
• Familiarity with AI or automation tools for data analysis and/or quality control.
• Experience in a global organization.