Shiny Mathew

DMX-BRS Aladdin File Delivery

• Worked on the migration and customization of an advanced ETL accelerator tool to align with client-specific requirements, leveraging technical expertise and collaboration.
• Enhanced the Data Quality feature using PySpark and Python, incorporating the Great Expectations library to generate detailed visual and CSV reports for bad records.
• Automated notifications for job statuses (failure, success, quarantined records) using Azure Logic Apps, improving monitoring efficiency.
• Executed data migration for 17+ inbound interfaces, creating backend transformation scripts using PySpark and Python to feed data into the BRS Aladdin platform.
• Developed and tested pipelines end-to-end on Azure Databricks, optimizing performance and scalability.
• Designed and implemented custom messages for 58+ interfaces, enabling seamless data transfer from ADC to PAM with PySpark, Python, and Spark SQL.
• Collaborated with clients and internal stakeholders to provide technical solutions, ETL tool expertise, and support for project enhancements.

BX Compliance Rule Coding

• Collaborated with a leading investment management firm to code compliance rules derived from IMA documents as inputs for a GenAI model.
• Developed and formatted compliance rule codes in JSON using the firm’s proprietary tools to support accurate model training and execution.

Datalink ETL Accelerator

• Developed and optimized a cloud-based ETL data migration tool, featuring capabilities such as data ingestion, transformation, quality assurance, and reconciliation.
• Designed and implemented a reusable ETL framework using PySpark to extract data from sources, including Azure Blob, S3, RDBMS, and Snowflake, incorporating JSON-configured mapping for source-to-destination consistency.
• Built a custom data reconciliation solution in PySpark, identifying and resolving data discrepancies during migration.
• Created an interactive UI with Streamlit and Python, enabling dynamic monitoring of data inconsistencies, and generating visual reports for mismatches.
• Integrated the Great Expectations library into the ETL tool to develop data validation and profiling features, producing actionable insights through detailed visual reports.
• Conducted root cause analysis, resolved 25+ bugs, and implemented 10+ change requests; executed unit testing to ensure high code coverage and reliability.