Engineered scalable data pipeline financial solutions, focusing on performance, stability, and data integrity.

Executed high-volume transformations using Python, leveraging Pandas and NumPy for efficient data transformations.

Optimized database solutions by partitioning, indexing, archival and tuning complex SQL queries across all system components.

Drove the end-to-end delivery as Capital Tenant Technical Lead for onboarding new regulatory data streams (Basel III, FINMA, and PRA reporting). Implemented and enforced Agile best practices (Scrum) including stand-ups & sprint/PI planning to maximize transparency & predictability across the book of work.

Enhanced the Big Data platform, focusing on custom, metadata-driven tools(low-code/no-code) for automated data ingestion, transformation, data quality, audit, logging and reporting using Python, Spark, Hive, Impala, and Kudu. Managed job orchestration using Control-M and Shell scripting, and enabled user data access through secured REST APIs.

Developed highly efficient, reusable, scalable Python/Spark scripts for data ingestion, resulting in 70% reduction in the team's delivery time for similar tasks. Optimized advanced SQL components to ensure reliable and low-latency handling of large-volume data within complex processing pipelines.

Served as the Application Owner, driving the technical strategic roadmap, resource allocation, and overall delivery for all new initiatives and maintenance within the TTS-Securities data offerings. Championed and enforced process optimization by focusing on lean documentation and driving the automation of regression test cases using reusable code repositories.

Led major technology upgrades (version upgrades) and executed the migration of legacy codebases to reusable Talend, successfully reducing operational costs by 40%. Devised rigorous data validation and error identification framework to ensure data reporting accuracy met the 99.9% standard within SLA.

Designed and tailored 20+ materialized views (ODS for intraday and batch data) to optimize data availability time by 70% for critical downstream systems and reports. Established a cross-application Break Fix core team and established triage protocols for reducing turnaround time for resolving time-critical production issues by 30%.

Architected and delivered the end-to-end Data Model (ERDs) and ETL pipelines for the Securities & Fund Services Datamart, for downstream applications and reports on MicroStrategy.

Designed and implemented reusable Ab-Initio framework (using psets), boosting standardization, developer productivity by 50% and reducing TAT and error rates. Managed cross-time zone delivery teams, ensuring project alignment with quality, cost, and architectural standards.

Developed an end-to-end automation framework utilizing Autosys and Conduct-it for job scheduling, monitoring and orchestration. Collaborated directly with Business Users and Program Managers to translate requirements into technical solutions and develop ODS/summary tables for downstream BI reporting.