Finance / Order-to-Cash Data Analyst

Finance / Order-to-Cash Data Analyst

Location: Remote

Rate: $70 on W2 

IP- Cognizant / End client details are confidential for now  

Role #1: Finance / Order-to-Cash Data Analyst

Ideal Background

• Experience at companies such as Airbnb, Uber, OpenAI, DoorDash, Stripe, Anthropic, or similar platform-based organizations.
• Strong Order-to-Cash (O2C) finance domain expertise.
• Strong SQL skills and analytics experience.
• Understanding of modern platform-based finance ecosystems rather than traditional ERP-only environments.

Responsibilities

• Certify and validate data pipelines.
• Perform reconciliation between operational systems and finance systems.
• Conduct data quality checks and validation.
• Work closely with finance stakeholders.
• Ensure datasets reconcile with the General Ledger and Oracle financial records.
• Support onboarding of new products and datasets into the data platform.
• Explain and defend data accuracy to the finance organization.

Key Takeaway This is not a pure data engineer role. It is a finance-savvy analyst who understands O2C processes, data reconciliation, and data validation in a modern technology platform environment.

Need 2 profiles:

1. Finance/O2C Analyst with strong SQL, reconciliation, and finance domain expertise from platform companies (Airbnb/Uber/OpenAI/Stripe type environments).

Role #1: Finance / Order-to-Cash Data Analyst

Ideal Background

• Experience at companies such as Airbnb, Uber, OpenAI, DoorDash, Stripe, Anthropic, or similar platform-based organizations.
• Strong Order-to-Cash (O2C) finance domain expertise.
• Strong SQL skills and analytics experience.
• Understanding of modern platform-based finance ecosystems rather than traditional ERP-only environments.

Responsibilities

• Certify and validate data pipelines.
• Perform reconciliation between operational systems and finance systems.
• Conduct data quality checks and validation.
• Work closely with finance stakeholders.
• Ensure datasets reconcile with the General Ledger and Oracle financial records.
• Support onboarding of new products and datasets into the data platform.
• Explain and defend data accuracy to the finance organization.