Devi Manoharan

Devi Manoharan is a senior Software Quality Engineering professional with 16+ years of experience delivering test strategy, automation modernization, and regulatory-grade validation for complex enterprise platforms. Her career spans manual, functional, and automation testing for web and client/server applications across both Agile and Waterfall models, with deep domain specialization in insurance and healthcare claims ecosystems. Manoharan’s technical identity is rooted in building scalable automation frameworks and data-validation systems that reduce release risk in environments where accuracy, compliance, and auditability are non-negotiable.

Her automation foundation centers on Selenium WebDriver with Java and modern test stacks—TestNG, Cucumber, Maven, and Jenkins—paired with strong data-centric validation practices. Across healthcare PBM, claims intake, and adjudication workflows, she has repeatedly operated where systems complexity is amplified by standards like HIPAA and EDI X12. Rather than treating quality as a downstream activity, she engineers quality into the lifecycle: automated reconciliation, schema enforcement, referential integrity checks, and end-to-end transaction validation that protects operational correctness.

At Arkansas Blue Cross Blue Shield, Manoharan served as a Senior Software Development Engineer in Test on a Federal Employees Program (FEP) claims intake rewrite—part of a mainframe modernization effort. Her work focused on designing and automating end-to-end claims processing for Dental, Professional, and Institutional claims, spanning the lifecycle from EDI ingestion through adjudication. She helped validate a complex integration surface that included DB2, SQL Server, Kafka, APIs, TIBCO, and a Smart Claims Router, ensuring that data flowed correctly across systems and that claim outcomes aligned with business and regulatory requirements. A core contribution was her Python-based, data-driven automation framework, built to support scalable regression and high-confidence validation of claims workflows. Through reusable modules and optimized data-driven components, she increased automation coverage by roughly 80%, identified and helped resolve over 100 data discrepancies involving denial codes, provider pricing, and EDI 837 processing, and reduced validation cycle time by integrating Kafka message validation into automated workflows. She also improved API testing efficiency for member eligibility and provider lookup through automated REST testing.

At the Federal Employees Program Operations Center (FEPOC) / CareFirst Blue Cross Blue Shield, Manoharan worked on NextGen 837 B2B standardization—validating claims processing across Medicare, Medicaid, Commercial, and Pharmacy domains. In this environment, she contributed across manual and automated testing, data validation, API testing, performance testing, and CI/CD integration within a multi-system architecture that included mainframe components, DB2, SQL Server, Kafka, APIs, TIBCO, Confluent Kafka, Red Hat AMQ, and SFTP-based workflows. She developed automated test scripts using Java/Selenium/Cucumber and built a BDD/ATDD hybrid automation framework with Maven-based structure. Her work expanded automation coverage and efficiency (approximately 80% improvement), improved ETL testing through source-to-target automation (about 70% gain), and reduced end-to-end ETL validation time by automating reconciliation and mapping validation. She also strengthened EDI transaction validation through automated schema and structural checks, increasing validation accuracy and reducing translation failures by catching defects earlier in B2B transformation maps.

In the PSHB member transition initiative at FEPOC/CareFirst, Manoharan focused on developing and enhancing automation pipelines that ensured accurate enrollment and claims processing—work that is critical to timely, correct member benefits. She architected scalable, HIPAA-compliant automation pipelines for EDI 834/837 workflows, increasing automation coverage by roughly 70–80% and reducing manual testing effort. By combining Python and Java automation with reconciliation logic, she cut enrollment/claims validation time by about half, reduced overall testing cycle time materially, and improved data accuracy through automated cross-system reconciliation. Her approach also enabled earlier detection of high-severity discrepancies before production deployment, reducing defect turnaround and protecting downstream operations.

Beyond delivery, Manoharan has contributed original work in healthcare quality engineering. She reports authoring a paper titled “A Multi-Layer Verification Framework for Ensuring Referential Integrity in Healthcare EDI Transaction Lifecycles,” and working on a patent related to an AI-generated synthetic EDI X12 data engine for high-volume claims testing and compliance simulation. Together, these efforts reflect a practical innovation focus: PHI-free synthetic test data at scale, coupled with multi-layer verification methods that preserve end-to-end referential integrity across healthcare EDI lifecycles—advancing both compliance readiness and test scalability.