# Data Analytics Engineer

**Company:** [Rippling](https://hotfix.jobs/companies/rippling)
**Location:** Dublin, Ireland
**Role:** Data Analytics
**Experience:** 4+ years
**Skills:** SQL, Python, Snowflake, Tableau, dbt, Dagster, ETL, Data Warehousing, Data Modeling, Data Reconciliation, Financial Reporting, Regulatory Compliance
**Posted:** 2026-07-30

> Analyzes payment flows and builds automated reporting, reconciliation, and dashboard solutions supporting finance, accounting, compliance, and product teams. Requires a relevant bachelor’s or master’s degree, 4+ years of large-dataset analytics experience, extensive SQL, and data warehousing or ETL expertise.

## Job Description

## 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, and other scripting or statistical tools.
- Develop real-time metrics dashboards to manage key financial and operating levers.
- Monitor payment flows between systems, banks, processors, and inter-company accounts.
- Perform daily account reconciliations and investigate discrepancies.
- React to emerging issues, summarize facts, and recommend timely resolutions for critical financial matters.
- Partner with Accounting, Compliance, Treasury, and other stakeholders to understand requirements and develop scalable reporting and reconciliation automation solutions.
- Develop internal tools and implement third-party tools where appropriate.
- Maintain comprehensive documentation of reconciliation processes and procedures.
- Prepare and deliver data and reporting solutions supporting month-end close, regulatory and compliance reporting, and internal and external audit reporting.
- Communicate findings and recommendations through clear presentations and reports.

## Requirements
- Bachelor's or master's degree in Computer Science, Engineering, Statistics, Data Science, Economics, Mathematics, Business Analytics, or a related field.
- **4+ years** of experience applying analytics engineering, analysis, modeling, or exploratory analysis to large datasets; experience in payments processing, quote-to-cash, or financial reporting is desirable.
- Experience with data warehousing, ETL, and reporting tools such as Snowflake, Tableau, dbt, or Dagster.
- Extensive experience with SQL across the data science development lifecycle, from initial analysis and model development through deployment.
- Experience working with engineering, finance, and accounting teams to assess data needs and build automated reporting pipelines.
- Strong problem-solving and communication skills, including the ability to communicate findings and recommendations to technical and non-technical audiences.
- Ability to work with multiple stakeholders and senior leadership.

## Nice-to-haves
- Experience with general accounting principles.
- Experience with the general ledger close process.
- Experience with regulatory compliance.

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