Deepshikha Agarwal

Senior Lead Software Enginner – Feb 2025– Till Date

Lead Software Enginner– Feb 2020– Jan 2025

Associate Vice President – Feb 2017 to Jan 2020

Associate– Feb 2013 to Jan 2017

Developer- March 2011 to Jan 2013

Major Contributions and Projects:

• Funds Assist, Enterprise GenAI Query Platform:

Spearheaded the conceptualization and delivery of a Generative AI–powered platform enabling natural language access to Asset Management fund data vi LLM-based Text-to-SQL capabilities.

Architected scalable Flask APIs deployed on AWS ECS, incorporating contextual conversation management, structured feedback loops, and governed data export functionality.

Designed a user activity logging and analytics framework, leveraging Qlik Sense dashboards to analyze usage patterns, improve model performance, and support iterative product enhancement.

• MCP Platform Enablement:

Collaborated and drive initiative to develop MCP servers using the MCP SDK(Wrapper on Fast MCP SDK), enabling developers to interact with Confluence, Jira, and Bitbucket through MCP client/Agentic Workflow.This enables AI-assisted planning, development, and knowledge access across the software lifecycle.As part of this initiative we also developed a standardized MCP framework enabling teams to rapidly build and deploy new MCP servers, accelerating adoption of AI-assisted workflows across engineering platforms.

• Qlik Data Onboarding, Dashboarding & Report Automation:Led onboarding of GFR data into Qlik Sense and developed advanced executive dashboards leveraging ODAG, Dynamic Views, and Dynamic Column Selection. Implemented report automation solutions to streamline recurring management reporting, reducing manual effort and improving data consistency. Partnered closely with senior stakeholders to continuously refine requirements, enhance user experience, and drive adoption of self-service analytics, onboarding of GFR data into Qlik Sense, and developed advanced executive dashboards leveraging ODAG, Dynamic Views, and Dynamic Column Selection. Implemented report automation solutions to streamline recurring management reporting, reducing manual effort and improving data consistency. Partnered closely with senior stakeholders to continuously refine requirements, enhance user experience, and drive adoption of self-service analytics.
• Cloud Data Migration & Batch Processing Architecture:
  Spearheaded ETL batch migration from legacy VSI systems to AWS, architecting a scalable and resilient cloud-native batch processing framework. Utilized AWS Lambda, RDS, S3, and ECS-based containerized Pentaho solutions to modernize data ingestion and transformation pipelines.Designed reusable components for error handling, inbound/outbound data orchestration, and secure MFT-to-S3 integration, improving maintainability, governance, and operational efficiency.
• TIF Cohort Lead: Take IT Forward (TIF) is a holistic, long-term career development initiative that supports the development, retention, and progression of woman technologists. Cohort Groups provide a community of support with peer-led discussion, learning and networking. Deepshikha led a cohort group of 50 women technologists.
• JIRA Dashboards/Reporting: Deepshikha is playing a role of scrum master apart from her technical responsibilities. She has built multiple dashboards and automated reports generation such as EPIC reports/Sprint Reports/Quarterly reports by KPIs using Pandas/Seaborn.
• Redesign ETL for Accounting DataMart: Originally ADAM was designed to have Dim Security primary key as Primary Asset Id and IMNT ID pair. Due to this combination, 99T, X-OUT and Identifier changes created security duplicates. The duplicate issue was resolved by flipping the dim security primary key from the combination of Primary Asset Id and IMNT ID to Eagle Security Alias and, all manual updates from Support team were eliminated.
• Platform Build and Enhancements: Deepshikha contributed in critical components of platform build such as unified graphql end points for SBS to integrate with Radix, history stitching across books, micro service to pre-process data to convert them into global model. Deepshikha is also working with CDOs, business stakeholders to standardize global holding/transaction data model based on business requirements.

• The Global Business Intelligence Team comprising ten members is responsible for developing, and maintaining the data-warehouse of Apple Inc.
• The project gathers data from all regions of Apple across the globe and puts it in the Global Data warehouse (GDW) using the ETL tool Informatica on a daily basis.
• The downstream DataMart pulls out a piece of required information using DB-links, XT-SNAP mechanism, and do some data massaging according to business requirements.

• The Special Effect finishes team is responsible for doing research on new components and developing paint formulations according to market requirements presented by marketing team.
• Post development of formulation, testing needs to be conducted to incorporate desired properties.
• Once passed from R&D, initial production support is required to generate large scale batch.