Financial Data Engineer

Likely ghost job

🕒 January 28

🇺🇸 United States – Remote

⏳ Contract/Temporary

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

Where this job comes from

Posted on Top Rpo's careers page, not through a job board

First seen by Remote Rocketship January 28

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Logo of Top Rpo

Top Rpo

11 - 50 employees

🎯 Recruiter

🤝 B2B

Recruitment • B2B

Top Rpo is a fast-paced, high-growth startup recruitment firm operating in the USA and India. It specializes in talent acquisition and Recruitment Process Outsourcing (RPO), offering end-to-end recruitment services including recruitment requirements and talent strategy development, sourcing, screening, interview scheduling, first- and second-round interviews, personality assessments, candidate selection, offer negotiation, background verification, onboarding, and KPI development. Top Rpo aims to streamline back-office hiring tasks so Hiring Managers can focus on interviewing and selecting the best candidates.

📋 Description

• Support the development of an in-house financial data extraction and modeling pipeline • Focus on programmatic extraction, normalization, and validation of financial data • Emphasize SEC EDGAR XBRL filings and automated, agent-driven workflows

🎯 Requirements

• Design and maintain in-house systems for extracting financial data from regulatory sources • Parse and normalize SEC EDGAR XBRL filings (10-K, 10-Q, 8-K) into structured, model-ready datasets • Work with XBRL components, including taxonomies, contexts, units, dimensions, and company-specific extensions • Build automated workflows for data ingestion, validation, reconciliation, and retry handling • Ensure consistency of financial data across periods, filings, and reporting entities • Support downstream financial modeling and analytics use cases

🏖️ Benefits

• Strong understanding of XBRL data structures and EDGAR filing architecture (required) • Practical experience in extracting and processing financial data from SEC EDGAR • Solid knowledge of financial statements and reporting concepts • Proficiency in Python for data extraction, transformation, and automation • Experience with libraries such as lxml, BeautifulSoup, pandas, requests, or similar tools • Experience building reliable and maintainable automation workflows

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