Financial Data Engineer

We are seeking a Financial Data Engineer to support the development of an in-house financial data extraction and modeling pipeline. This role focuses on programmatic extraction, normalization, and validation of financial data, with a strong emphasis on 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, Beautiful.

Soup, pandas, requests, or similar tools ● Experience building reliable and maintainable automation workflows ● Preferred Qualifications: ● Exposure to agentic or LLM-based workflows for document processing or data validation ● Familiarity with additional financial or regulatory data sources ● Experience with data modeling or analytical pipelines Key Focus: This role requires a practical understanding of how financial data is structured, reported, and extracted at the source level, particularly within XBRL-based regulatory filings.