Accounting transformation associate

The Accounting Data Analyst supports key transformation initiatives by leveraging data, analytics, and process insights to improve the accuracy, efficiency, and scalability of the Accounting organization. This role will partner closely with Accounting, Finance, Technology, and cross‑functional stakeholders to build analytical solutions, streamline workflows, and enhance data integrity across core processes. The ideal candidate blends strong analytical and technical skills with an understanding of accounting concepts, an eye for process improvement, and the ability to communicate insights clearly.

• Build, enhance, and maintain datasets, dashboards, and reporting solutions that support accounting close, reconciliations, and key operational metrics.
• Perform detailed data analysis to identify trends, anomalies, and root causes affecting accounting outcomes.
• Support the development of forecasting models, variance analytics, and data quality checks.
• Automate routine reporting or data‑preparation tasks to improve efficiency and reduce manual work.
• Accounting Process Support:
  Analyze end‑to‑end accounting workflows to identify process gaps, redundancies, and opportunities for optimization or automation.
• Support journal entry and reconciliation improvements through data‑driven insights.
• Collaborate with Accounting SMEs to translate process needs into functional data requirements.

• Partner with Technology teams to contribute to system enhancements, integrations, and data‑mapping efforts.
• Support testing, validation, and user acceptance for new tools, automated workflows, and system changes.
• Document data flows, process maps, and reporting logic for transparency and future scalability.

• Work closely with Accounting Transformation leadership to prioritize analytics and process‑improvement initiatives.
• Communicate findings, insights, and recommendations in a clear, structured way to both technical and non‑technical stakeholders.
• Help establish best practices for data governance, consistency, and quality across the accounting ecosystem.

For this U.S. based position, the expected compensation range is $86,400 - $129,600 per year and an additional uncapped commission.

The compensation range for this full‑time position applies to candidates located within the United States. Our salary ranges are determined by reviewing roles of similar responsibility and level. Within the salary range, individual pay is determined by several factors including performance, knowledge, job‑related skills, experience, and relevant education or training. Schneider Electric also offers a comprehensive benefits package to support our employees, inclusive of medical (with member reward points), dental, vision, and basic life insurance, Benefit Bucks (credits to apply towards your benefits), flexible work arrangements, paid family leaves, 401(k) + match, well‑being and recognition (including service anniversary) programs, 12 holidays per year, 15 days of paid time off per year (pro‑rated in the first year of employment based on start date), opportunity to purchase company stock (eligibility depends on start date), and military leave benefits.

• Bachelor’s degree in Accounting, Finance, Data Analytics, or related field.
• 2–4+ years of experience in accounting, financial analysis, data analysis, or a similar hybrid role.
• Strong Excel and data‑manipulation skills.
• Experience with data analytics tools (e.g., Power BI, Tableau, Alteryx, SQL, Python — based on organization preference).
• Understanding of core accounting principles (e.g., accruals, journal entries, reconciliations, GAAP fundamentals).
• Ability to synthesize data into clear narratives and visuals for decision‑makers.
• Strong attention to detail, critical thinking, and problem‑solving ability.

• Experience supporting transformation, process improvement, or system implementation projects.
• Familiarity with ERP systems (e.g., SAP, Oracle, Workday) and accounting data structures.
• Experience automating or optimizing workflows. Comfort…