Mamatha Reddy

About Mamatha Reddy

I am a Palantir Foundry Developer with a passion for building scalable, business-driven solutions that optimize data workflows and enhance decision-making. My expertise lies in Solution Design, where I identify organizational needs and document processes using Foundry\'s Solution Designer to align technical implementations with business objectives.I specialize in: Ontology Management – Structuring and managing complex datasets for seamless integration and operational efficiency. Code Repositories – Designing and optimizing scalable Foundry applications across multiple business use cases. Automation & Process Optimization – Enhancing workflows through automation and real-time data orchestration.When developing reporting tools, I leverage the right Foundry application based on specific business needs: Workshop – For interactive, user-driven applications. Contour – For efficient dataset-level reporting and visual insights. Quiver – For advanced analytics on time-series and object-level data.Beyond application development, I have hands-on experience integrating external systems with Foundry, managing batch and streaming data pipelines, and conducting health checks on millions of dynamic tables to ensure system integrity and performance.I thrive on solving complex data challenges and am always eager to collaborate with professionals and organizations seeking robust, scalable data solutions that drive business value. Let\'s connect!

Experience

1. Palantir Data Engineer Aws

   Entergy

   Oct 2024 — Present · Houston, TX, US

   Designed and implemented an operational semantic layer using Palantir Foundry Ontology Manager, modeling core utility billing entities including accounts, bills, tariffs, rate categories, and rate steps.• Defined relationships and ActionTypes to support business workflows and eliminate direct dependency on raw relational datasets.• Built ingestion pipelines in Pipeline Builder to load SAP billing data and external sources from AWS S3 into Foundry’s raw and refined layers.• Developed production transformation logic in Code Repositories using Python, PySpark, and Foundry Transformation Language (FTL) to generate tariff calculations and structured rate outputs.• Validated datasets and calculation logic using Code Workbooks prior to pipeline deployment.• Verified object relationships and business behavior using Object Workbooks to ensure ontology accuracy.• Created a user-facing operational application in Workshop allowing business users to upload billing data and trigger ontology-driven actions.• Optimized long-running Spark transformations, reducing pipeline runtime by 30–40% using partitioning and caching strategies.Implemented scheduled builds and dependency triggers using Automate and Active Pipelines.• Integrated AWS monitoring (CloudWatch) and incident workflows for operational reliability and root-cause analysis.• Enforced governance using data lineage, access policies, and curated datasets.

Education

• Southern University and A&M College- Baton Rouge

  Master of Science, Computational Science