Enterprise Data Platforms • Financial Systems • AI Governance
Hello! I’m Alan Palayil👋
Data Engineer at Genworth Financial,
engineering investment accounting data pipelines where correctness and reliability aren’t optional.
Ph.D. student in AI and Data Science.
Own the full technical lifecycle of CML and Derivatives investment-accounting systems — architecture, data engineering, Azure cloud modernization, and production stability for enterprise financial platforms.
Own end-to-end data engineering for CML and Derivatives accounting in PAM: architecture decisions, enhancement roadmap, production support, data validation, and vendor coordination.
Operate and extend the JSON message-generation platform (V1–V7) running daily against active commercial mortgage loans across DEV/UAT/PROD with versioned releases and built-in source-to-destination reconciliation.
Design and deploy cloud-native data pipelines on Azure Synapse Analytics and Azure Data Lake Storage as part of ongoing migration of legacy investment-accounting infrastructure to cloud-hosted architecture.
Engineer production automation covering file-transfer, monitoring, retry, dependency management, and notification — systematically reducing manual intervention across Investments Operations workflows.
Serve as primary engineering interface to Accounting, Controllership, Infrastructure, QA, and third-party vendors, driving alignment between data engineering deliverables and financial reporting requirements.
Led engineering and modernization of investment-accounting systems — initiating the CML-to-PAM migration, launching the Derivatives-to-Azure rehosting project, and expanding platform ownership into enterprise data engineering scope.
Initiated and led the CML-to-PAM migration and Derivatives-to-Azure rehosting projects, taking full application ownership after the P1 to P2 progression.
Contributed to PAM Legacy Message Generator rehosting — technical design, mapping validation, integrity testing, and performance tuning for the Findur → PAM transition.
Developed Python, SQL, ETL, and JSON engineering solutions supporting CML workflows spanning loan, collateral, fee, payment, interface, and reconciliation processing.
Investigated production incidents through root-cause analysis; implemented sustainable fixes improving system reliability, auditability, and user experience.
Partnered with cross-functional operations, accounting, platform-support, and technology teams to align engineering deliverables with financial reporting requirements.
Built Python and SQL automation for investment accounting workflows across Fixed Income, Derivatives, and CML, replacing manual processes with production-grade pipelines and interfaces.
Automated financial reporting and data extraction pipelines in Python and SQL, reducing manual workloads and data entry errors across accounting workflows.
Maintained Investments Trading & Accounting platforms (PAM Accounting, Markit EDM, and AppWorx), ensuring system uptime and performance.
Resolved application and data failures through root cause analysis, developing permanent fixes to eliminate recurring production issues.
Developed system interfaces with Accounting and Operations teams to ensure reliable data flow across Fixed Income, Derivatives, and CML.
Supported core accounting workflows across multiple asset classes, providing technical assistance and troubleshooting for daily production tasks.
Engineered custom TCP/IP protocols and IoT control systems to replace restricted third-party platforms, and built real-time data pipelines with web-based monitoring interfaces.
Developed custom TCP communication layers without external automation software, increasing system control and reducing platform dependency.
Built an IoT street lamp prototype using C# and MQTT to enable low-latency communication between hardware and the cloud.
Created a web-based dashboard using HTML, CSS, and JavaScript for direct real-time monitoring of backend system data.
Collaborated with senior engineers to design, test, and document system requirements and user guidelines.
Integrated frontend interfaces directly with backend communication services to ensure immediate data synchronization.
I build data infrastructure for financial systems and research AI governance at the doctoral level.
If you're working on similar problems, I'd enjoy the conversation.
