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Tier-1 employer, generalist senior software/data title, and broad skillset requirements drive high competition.
Core scraping and data engineering skills are transferable, but healthcare payer domain knowledge favors industry experience.
Specific mandatory technical skills (Python, scraping, parsing, ETL) and domain expertise increase screening strictness.
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Design, develop, test, deploy, and maintain robust web scraping and RPA solutions for extracting healthcare payer policy data from diverse formats (HTML, PDFs, Excel, Word).
Build and enhance scalable data pipelines and ETL/ELT processes to normalize and deliver structured policy metadata and authorization rules across multiple payer domains.
Lead solution engineering to integrate systems, maximize automation, apply AI/ML techniques, ensure data quality, and monitor pipeline reliability.
Advanced experience with XPath, CSS selectors, regular expressions, and web scraping frameworks (e.g., Selenium, Playwright, Scrapy).
Proficient programming skills in Python (preferred) or C#; solid knowledge of HTML, DOM, JavaScript rendering, and XML/JSON schema design.
Experience in designing data models and cross-domain integration pipelines; familiarity with ETL/ELT processes, cloud storage (AWS S3 or Azure), and API integrations.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in end-to-end data engineering within healthcare payer environments, especially dealing with prior authorization and policy ingestion workflows.
Capable of independently managing full data lifecycle projects including bot development, data transformation, solution scaling, and automation of complex extraction tasks.
Skilled in applying analytical rigor to break down large datasets, enforce data standards, and implement secure, high-quality data pipelines in a regulated domain.