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Information Technology - Artificial Intelligence
(Gold Winner)

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#TBA04213

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Paid

PO Created Date

2025-02-18 17:13:53

Paid Date

2025-02-18 17:14:39

Competition

2025

Season

Entry ID

TBE104673

Entry Submission Date

2025-02-18 17:10:40

Member's Name

Shishir Tewari

Member's Email

tewarishishir@gmail.com

Entry Level

Information Technology

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IT25008 - Artificial Intelligence

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Project Description

Shishir Tewari is a Senior Engineering Manager at Procore Technologies, bringing 19 years of expertise in data engineering, AI/ML, and cloud analytics. With a distinguished career spanning leadership roles at Google, Amazon, and Morgan Stanley, Shishir has been at the forefront of transforming data platforms with cutting-edge AI innovations. His work focuses on building scalable, high-performance data ecosystems that drive business intelligence, data governance, and predictive analytics.

Recognizing the challenges of traditional rule-based data clustering, Shishir pioneered AI-Driven Data Clustering, a groundbreaking innovation that leverages machine learning to optimize data classification, deduplication, and pattern detection in big data environments. This approach replaces static, manually curated rules with self-learning models, significantly improving accuracy, scalability, and adaptability. By harnessing AI, the solution dynamically refines clustering techniques, reducing false positives and enhancing data integrity.

This innovation has profound implications for businesses dealing with large and complex datasets, enabling them to derive actionable insights with unprecedented precision. AI-Driven Data Clustering streamlines data management accelerates processing speeds, and unlocks new opportunities for automation in decision-making. Its impact extends to industries such as finance, construction, and e-commerce, where high-quality, structured data is critical for analytics and forecasting.

As a thought leader in AI-powered data engineering, Shishir continues to drive technological advancements that shape the future of big data. His expertise in AI/ML integration, coupled with a deep understanding of enterprise data challenges, positions him as a leading innovator in the Artificial Intelligence space. Through his work, Shishir is redefining how businesses harness AI to unlock the true potential of their data.

Project Description for Judges

Question 1 : Provide a brief description / background of your nominated organizational, departmental, team, or individual circumstance. (Your response to this question will be used for public display if your entry is awarded.)

This innovation has profound implications for businesses dealing with large and complex datasets, enabling them to derive actionable insights with unprecedented precision. AI-Driven Data Clustering streamlines data management, accelerates processing speeds, and unlocks new opportunities for automation in decision-making. Its impact extends to industries such as finance, construction, and e-commerce, where high-quality, structured data is critical for analytics and forecasting.

Question 2 : Outline your nominated organizational, departmental, team, or individual achievements, dated 1-3 years prior, based on your selected categories.

Over the past three years, Shishir Tewari has led significant advancements in AI-driven data engineering, focusing on developing scalable, high-performance data platforms and AI/ML-powered solutions. His contributions have transformed data management and analytics across multiple organizations, driving efficiency, automation, and intelligent decision-making.

Key Achievements (2022–2025):
-AI-Driven Data Clustering Innovation
Spearheaded the AI-Driven Data Clustering initiative at Procore Technologies, enhancing data accuracy and scalability.
Replaced traditional rule-based clustering with machine learning models, achieving a 30% improvement in clustering accuracy and reducing manual data reconciliation by 40%.

- Next-Generation Master Data Management (MDM) Platform
Designed and implemented a next-gen MDM data platform leveraging AI/ML, improving data governance, deduplication, and accessibility.
Ensured enterprise-wide data consistency, enabling real-time insights for business teams.

-Cloud Data Engineering & Migration Excellence
Led the enterprise data warehouse migration from Snowflake to Databricks, optimizing performance and reducing costs.
Developed scalable data pipelines that improved data processing efficiency and AI model training speeds.

-High-Impact Leadership & AI Strategy Execution
At Google, managed the Google Finance Data Universe, leading a team of 15+ engineers and optimizing financial data pipelines that reduced processing times by 90%.
At Amazon, built big data infrastructure for advertising analytics, reducing cloud storage costs by 80%.

-Thought Leadership & AI Advocacy
Published insights on AI’s role in data clustering and governance, contributing to industry best practices.
Mentored engineers on leveraging AI/ML in enterprise data solutions, fostering a culture of AI innovation.
Through these achievements, Shishir has redefined AI-powered data engineering, showcasing how machine learning can revolutionize clustering methodologies, enhance data integrity, and drive business success in AI-first enterprises.

Question 3 : Provide examples of the strategies / plans you have introduced, in order to attain your nominated organizational, departmental, team, or individual achievements. Explain why the highlighted achievements are significant / unique.

Shishir Tewari has introduced strategic AI-driven approaches to transform data clustering, governance, and enterprise-scale analytics. His AI-Driven Data Clustering initiative and cloud data modernization efforts have significantly improved accuracy, efficiency, and scalability in data engineering.

Key Strategies & Plans Introduced:
1. AI-Powered Data Clustering
Strategy: Transitioned from static, rule-based clustering to machine learning-driven models for improved accuracy and adaptability.
Execution: Developed self-learning AI models using unsupervised learning algorithms (e.g., K-Means, DBSCAN) to dynamically detect patterns in massive datasets.
Impact: 30% increase in clustering accuracy and 40% reduction in manual data reconciliation.
Enabled real-time anomaly detection, improving data integrity across business operations.

2. AI-Driven Master Data Management (MDM) Platform
Strategy: Designed a centralized, AI-powered MDM framework to ensure high data accuracy and governance.
Execution: Integrated AI-based data deduplication and entity resolution, reducing redundant records.
Established real-time data monitoring with automated data quality assessments.
Impact: Enhanced data integrity, eliminating inconsistencies and improving analytics reliability.
Allowed cross-functional teams to access clean, unified data, boosting decision-making.

3. Cloud Data Engineering & Migration
Strategy: Led migration from Snowflake to Databricks, optimizing cloud performance and cost.
Execution: Redesigned ETL pipelines with Spark & Delta Lake, improving processing speeds by 50%.
Impact: Accelerated AI model training and enhanced data accessibility for business users.

Significance & Uniqueness:
Industry-first AI-driven clustering, improving automation and business intelligence.
Eliminated data duplication, reducing costs and enhancing decision-making.
Scalable AI architecture, future-proofing enterprise data management.

Shishir’s innovations demonstrate how AI can revolutionize data engineering, making big data processing more intelligent, scalable, and business-driven.

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