
Required Skills & Tech Stack
Data validation
Quality assurance
Accounting fundamentals
Financial data analysis
Microsoft Excel
SQL basics
Python basics
Attention to detail
Analytical thinking
Problem solving
English communication

Eligibility Criteria
• Minimum: Bachelor’s degree or higher (any discipline). Preferred streams: Accounting, Finance, Business, Statistics, Computer Science or related fields.
• Academic performance: Typically 60% or above (or CGPA 6.0/10) in the qualifying degree.
• Batch: Recent graduates up to 2 years post‑graduation.
• No active backlogs at the time of joining; any pending backlogs must be cleared before the start date.
• Internship or project experience in accounting, bookkeeping, invoice processing, ERP usage, or financial data QA is strongly preferred.
• Strong command of written and spoken English.

Job Description & Key Responsibilities
YipitData is a fast‑growing market research and data‑analytics firm that helps investors, corporations and consultancies turn massive, unstructured data sets into clear, actionable insights. Headquartered in New York with a strong global footprint, the company operates a suite of SaaS platforms that ingest, cleanse, and model data from public filings, credit card transactions, and other proprietary sources. Its culture blends rigorous analytical thinking with a startup‑like agility, offering employees exposure to cutting‑edge data pipelines, cloud‑based infrastructure, and cross‑functional collaboration. YipitData’s commitment to data integrity makes it a trusted partner for Fortune‑500 clients looking to make data‑driven decisions.
The Data QA Associate role is a full‑time, work‑from‑home position based in India. As a junior member of the SpendHound team—a SaaS solution that helps businesses monitor and optimise software and cloud spend—you will be the gatekeeper of data quality. Your day‑to‑day responsibilities revolve around validating financial records, spotting inconsistencies, and ensuring that every expense entry is accurate and compliant with internal standards. This role is ideal for fresh graduates or candidates with up to two years of experience in accounting, bookkeeping, or financial data quality assurance.
Key responsibilities include:
1. Review and validate vendor invoices, bills, and payment records against source documents.
2. Verify the correctness of financial transaction amounts and expense categories.
3. Detect and flag duplicate, incomplete, or inconsistent data entries.
4. Investigate root causes of data quality issues and propose corrective actions.
5. Update and maintain accurate vendor‑to‑spending‑category mappings.
6. Collaborate closely with data engineers, product managers, and finance teams to resolve data anomalies.
7. Document validation procedures and maintain audit trails in line with data‑security policies.
8. Participate in periodic data‑quality audits and contribute to continuous‑improvement initiatives.
9. Assist in onboarding new ERP integrations by reviewing data ingestion pipelines.
10. Provide timely status updates to stakeholders on data‑quality metrics.
Technical stack: Microsoft Excel (advanced functions, pivot tables), basic SQL for querying relational tables, introductory Python for scripting simple validation checks, and familiarity with ERP systems such as SAP, Oracle, NetSuite or QuickBooks Online. The role also leverages internal data‑quality dashboards built on Tableau or PowerBI.
Growth path: Starting as a Data QA Associate, high performers can progress to Senior Data Quality Analyst, then to Data Quality Lead, and eventually into Data Operations Manager or Product Analytics roles. The exposure to finance‑focused data pipelines and cross‑functional teams equips you with a strong foundation for a career in data analytics, finance operations, or product management.
Why join YipitData? You will work on a mission‑critical product that directly influences corporate spend optimisation, gain hands‑on experience with real‑world financial data, and enjoy the flexibility of a fully remote role while being part of a globally recognised analytics brand. The company offers mentorship, regular learning sessions, and a performance‑driven culture that rewards accuracy and proactive problem‑solving.