Deepak Gaur
- Role
- Ai Data Principal Engineer at Cognizant
- Location
- New Delhi, IN
- LinkedIn followers
- 500 followers
About Deepak Gaur
Experienced Data Engineer with over six years in Big Data, Cloud Computing, and ETL…
Experience
Ai Data Principal Engineer
Dec 2023 — Present
SENIOR ASSOCIATE PROJECTS -*Agentic AI, Platforms and Data Engineering Designed and implemented an AI-assisted revenue shortfall detection system to analyze complex enterprise contracts with product-based and conditions-based revenue commitments. Built ingestion pipelines to process contract terms, thresholds, timelines, and condition rules, enabling automated evaluation of revenue fulfillment. Developed a configuration-driven shortfall calculation engine, allowing different contract structures and rules to be evaluated without code changes. Implemented an agentic AI orchestration layer to coordinate contract analysis, rule interpretation, and shortfall computation workflows. Designed and exposed modular APIs for contract ingestion, configuration management, shortfall calculation, and downstream consumption. Built a core domain layer encapsulating contract logic, revenue aggregation, and condition evaluation for correctness and explainability. Integrated event driven processing using Pub/Sub to trigger recalculations and downstream notifications asynchronously. Ensured full traceability, auditability, and explainability of AI-assisted decisions for financial and contractual reporting.*Enterprice Data Load and Migration framework Designed and implemented a modular, enterprise-grade data load and database migration framework to standardize schema changes, data loads, and post-deployment validation. Integrated automated unit and framework-level testing using PyTest to validate data logic, schema correctness, and pipeline behavior.*Metadata driven Data Ingestion and Warehouse Automation Built end to end metadata driven data pipelines using Apache airflow and Python, enabling dynamic DAG generation and scalable onboarding of new datasets. Built configuration driven SQL execution and orchestration frameworks to automate data loading, transformation, truncation, and reconciliation workflows.
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