Sai Sandhya K.

About Sai Sandhya K.

I work primarily across financial data and reporting systems, with a strong focus on building reliable data pipelines that can support real financial analysis. A major part of my recent work has been building a universal SEC financial statement reconstruction pipeline from raw filing data. The system is designed to rebuild the core statements so that the values, labels, tags, structure, and presentation stay as close as possible to the original SEC filings. I built it as a non-hardcoded architecture intended to work across nearly companies, and I am currently extending the same logic from annual 10-K filings to quarterly filings. I’m also working on a point-in-time financial data platform focused on preserving financial facts as they were known at a given moment, with history, validation, and as-of query support built into the workflow. Alongside that, I’ve also worked on KPI reporting, dashboard-driven analysis, and business-focused data projects using SQL, Python, Power BI, and Excel. So while my main strength is in backend financial data and reporting logic, I can also work on the business-facing side to turn data into reporting, insights, and decision support.

Experience

1. Financial Data Analyst

   Omnesys Technologies, Inc

   Mar 2026 — Present · Delray Beach, FL, US

   Built and led a universal SEC financial statement reconstruction engine that transforms raw filing data into statement-faithful outputs across companies.Designed the system to recover the correct values, row labels, tags, structure, and presentation flow required to match reported SEC filings as closely as possible, rather than generating simplified analytical summaries.Led the reconstruction and validation workflow end to end, solving high-difficulty problems in filing interpretation, statement logic, period and context selection, structural alignment, and cross-company reporting differences.Built the architecture as a scalable, non-hardcoded system intended to work across nearly companies, and am currently extending the same logic from annual filings to quarterly filings.