Data Analyst

RGP•New York, NY

7d•$90 - $100•Remote

About The Position

RGP is seeking a hands-on Snowflake Data Analyst to support a high-volume financial data environment during an audit preparation initiative. The analyst will take ownership of Python-based data extraction currently handled by the Corporate Controller and work directly with finance, accounting, technical, and executive stakeholders. This is a specialized financial-data role, not a general analytics position, and involves processing approximately 780,000 invoices annually and millions of underlying transaction lines. The role supports audit preparation by extracting, validating, and analyzing financial and transactional data stored in Snowflake; taking ownership of Python scripts that transfer data from Snowflake into the accounting system; and writing and optimizing complex SQL queries. The analyst will review and enhance extraction processes for accuracy, reliability, and audit readiness, working across an interconnected environment that includes change data capture, Snowflake, Python, and downstream accounting systems. The position also requires translating financial and audit requirements into practical data solutions and clearly communicating findings, risks, dependencies, and technical issues to technical and nontechnical audiences. Broader enterprise data transformation initiatives may follow the initial audit assignment. The position is fully remote in the United States and requires availability during Eastern Time hours. It is a full-time contract initially lasting through the end of March, with potential for extension. The target pay range is $90–$100 per hour, W2.

Requirements

Strong hands-on experience with native Snowflake development and data operations.
Advanced SQL skills, including querying and validating large datasets.
Strong Python scripting experience, particularly for data extraction, transformation, and system-to-system data movement.
Direct experience processing high-volume financial, accounting, invoice, or transactional data.
Experience with large-scale transactional systems or accounting-system integrations.
Ability to validate data completeness, accuracy, and consistency for audit or financial reporting purposes.
Demonstrated experience working in fast-paced finance or accounting environments.
Strong stakeholder-management and client-facing communication skills.
Ability to explain technical concepts directly, clearly, and concisely.
Professional maturity and executive presence.
Ability to work independently, own deliverables, and navigate demanding stakeholder expectations.
Availability to work Eastern Time hours.

Nice To Haves

Experience supporting financial audits, audit readiness, or financial-data reconciliation.
Experience transferring data between Snowflake and ERP, accounting, or financial reporting systems.
Familiarity with change data capture environments.
Experience improving or taking ownership of Python scripts originally developed by finance or accounting stakeholders.
Background supporting organizations with large invoice volumes and millions of transaction-level records.
Experience with enterprise data transformation or financial-data modernization initiatives.
Ability to support evolving data needs beyond the initial audit engagement.

Responsibilities

Extract, validate, and analyze financial and transactional data in Snowflake for audit preparation.
Take ownership of existing Python scripts used to transfer data from Snowflake into the accounting system.
Write and optimize complex SQL queries to retrieve large volumes of financial data.
Review and improve data-extraction processes for accuracy, reliability, and audit readiness.
Work across change data capture, Snowflake, Python, and downstream accounting systems.
Process data associated with approximately 780,000 invoices annually and millions of transaction lines.
Partner with finance, accounting, technical, and executive stakeholders.
Translate financial and audit requirements into practical data solutions.
Communicate findings, risks, dependencies, and technical issues clearly to technical and nontechnical audiences.
Potentially support broader enterprise data transformation initiatives after the initial audit assignment.