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.

● 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

● 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

● 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.