Shivam Mathur

About Shivam Mathur

As a Data Management Professional at LPL Financial, I leverage my expertise in data management and analytics to support the financial crimes detection systems of TD Bank, Bank of America, and Wells Fargo Bank. With over 20 years of experience in this role, I have successfully implemented data-driven risk assessments, developed AML models, enhanced governance on data assets, and designed data pipelines to optimize data processing efficiency.I hold a Bachelor of Arts degree in Accounting and Computer Science from the University of Delhi and am a Certified Fraud Examiner (CFE) issued by the Association of Certified Fraud Examiners (ACFE). I have also completed courses in Data Science and Open Source tools for Data Science from Coursera. My skills include XML, Business Analysis, and Requirements Analysis, design and develop data solution. I am passionate about using data to drive business strategy, efficient data solutions and operational improvements, introduce AI and ML where it can add efficiency, and I enjoy collaborating with cross-functional teams to identify critical data insights.

Experience

1. Lead Developer

   LPL Financial

   Jan 2025 — Present

   Architected and executed the migration of legacy Neo4j workloads to AWS Neptune, including the refactoring of Cypher logic into optimized OpenCypher queries for high-performance graph traversals.• Engineered Neptune GraphDB infrastructure using Terraform (IaC), managing the full lifecycle of Neptune Cluster creation, instance scaling, and the integration of Neptune Analytics for fast memory-optimized graph queries. • Developed complex business logic by embedding parameterized OpenCypher queries within Python-based microservices, enabling dynamic interaction with the graph schema.• Designed and deployed scalable ETL pipelines using AWS Glue and PySpark to ingest, transform, and load massive datasets from S3 into Neptune GraphDB.• Orchestrated serverless workflows using AWS Step Functions and Lambda to automate data ingestion, Glue Crawlers for schema discovery, and cross-service coordination.• Leveraged AWS SageMaker AI to develop, train, and deploy machine learning models, integrating graph features (node embeddings/centrality) to enhance predictive accuracy.• Optimized development velocity by utilizing GitHub Copilot for accelerated Python unit test generation, complex debugging, and code refactoring.

Education

• Delhi University

  Bachelor of Arts - BA, Accounting and Computer Science

  1999 — 2002