Analytics Engineer - Payments

About the role

Ripping's Payments Data & Analytics team is seeking an experienced and highly skilled Analytics Engineer - Payments to join our rapidly expanding team. This role involves designing, building, and maintaining services that process vast amounts of financial data, providing comprehensive visibility into every stage of the money movement lifecycle within Rippling's payments product ecosystem.

Responsibilities

• 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.
• 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.

Requirements

• 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.

Qualifications

• 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.

Skills

• 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.

Benefits

• Competitive salary + benefits + equity.
• Flexible work schedule, including the option to work from home.
• Health insurance, including medical, dental, and vision coverage.
• Retirement savings plan with company match.
• Employee discounts on Rippling products and services.
• Professional development opportunities and training programs.
• Regular team-building activities and social events.
• Work-from-home options for eligible employees.

Pay

• A variety of factors are considered when determining someone’s compensation–including a candidate’s professional background, experience, and location. Final offer amounts may vary from the amounts listed below.
• The pay range for this role is: 114,000 - 199,500 USD per year (US Tier 1)

Schedule

• Office-based employees (employees who live within a defined radius of a Rippling office) are required to work in the office, at least three days a week under current policy.