Senior Data Analyst (Payments)

Rippling gives businesses one place to run HR, IT, and Finance. It brings together all of the workforce systems that are normally scattered across a company, like payroll, expenses, benefits, and computers. For the first time ever, you can manage and automate every part of the employee lifecycle in a single system.

• →Collaborate cross-functionally with engineering, accounting, financial partnerships, and product teams to analyze and account for billions of dollars flowing through the Rippling payment platform.
• →Build full-cycle analyses using SQL, Python, or other scripting and statistical tools, and develop real-time metrics dashboards to manage key financial and operating levers of the business.
• →Monitor payment flows between systems, banks, processors, and inter-company accounts, perform daily account reconciliations, and follow up on any discrepancies.
• →React swiftly to emerging issues, summarize facts, and provide recommendations for the timely resolution of critical financial matters.
• →Collaborate with key stakeholders (Accounting, Compliance, Treasury, etc.) to understand business requirements and develop scalable solutions for reporting and reconciliation automation, including internal tool development and/or the implementation of third-party tools.
• →Develop and maintain comprehensive documentation of reconciliation processes and procedures.
• →Prepare and deliver data and reporting solutions supporting month-end close, regulatory & compliance reporting, and Internal and External Audit reporting.
• →Communicate findings and recommendations to stakeholders through clear and concise presentations and reports.

• →Master’s degree or Bachelor's degree in Computer Science, Engineering, Statistics, Data Science, Econ, Math, Business Analytics, or other related fields.
• →4+ years of demonstrated experience in applying analytics engineering, analysis, modeling, and/or exploratory analysis to large datasets, ideally in payments processing, quote-to-cash, or financial reporting.
• →Experience with data warehousing, ETL, and reporting tools (e.g. Snowflake, Tableau, dbt, Dagster).
• →Extensive experience with SQL and its application to all phases of the data science development process (initial analysis and model development through deployment).
• →Experience working with engineering, finance, and accounting teams to assess their data needs and build automated reporting pipelines.
• →Strong problem-solving and communication skills, with the ability to communicate findings and recommendations clearly to both technical and non-technical audiences.
• →Ability to interface with multiple stakeholders and senior leadership (C-suite) across the organization.
• →Bonus points if you have experience with general accounting principles, the general ledger close process, and regulatory compliance.