Madhur Sawhney

Leading the strategic development and implementation of Walgreen’s enterprise data and AI architecture, advancing capabilities in real-time analytics, AI/ML pipeline integration, and cloud-native data platforms that are fundamental to promoting innovation within retail operations and healthcare transformation. Principal accomplishments in architecting scalable, secure, and insight-oriented platforms at the intersection of cloud computing, AI, and consumer engagement encompass the following: • Real-Time Data Pipelines & Event Architecture • Secure, Scalable Data Lakes & Warehousing • Advanced Analytics & Decision Intelligence Dashboards • AI/ML Platform Engineering & MLOps • Agentic & Generative AI Use Case Enablement • Data Governance & Interoperability Readiness

Responsible for the full spectrum of data capabilities, including analytics, data science, ML & AI products, data engineering, Data & ML Ops, data warehousing and business intelligence, heading a global team with services in over 15 countries. The capabilities deployed resulted in an additional multi-million revenue stream attributed directly to advanced analytics and AI capabilities. • Deployed a custom machine learning platform incorporating vector stores, embeddings, feature stores and LLM frameworks that powers product features such as semantic search, packaged recommendations, propensity modeling, opportunity sizing, media mix modeling and A/B testing. • Modernized the analytics infrastructure by introducing microservices, event-driven platforms, real-time data streaming, Lakehouse architecture, and infrastructure as code to enable self-serve analytics that support customer experience, product strategy, and quantifiable business outcomes. • Created a go-to-market plan and services roadmap, introducing a premium subscription tier with advanced analytics and AI features to drive growth and revenue.

Head data engineering, data & ML platforms, applied sciences, business intelligence, advanced analytics, data governance efforts and global teams to drive direct to consumer streaming subscription product services spanning 12 global launches, stewarding a budget portfolio of $35M with efforts resulting in 12% revenue growth and an uptick of 26% in consumer engagement and retention. • Implemented Enterprise Lakehouse architecture, ML platform and analytics framework supporting content, product, design, marketing, ad sales, research, CRM, and finance organizations. • Deployed scalable and resilient compute layer for real time streaming events, processing all user engagement data enabling content recommendations, improving user experience, and personalizing placements resulting in increased customer engagement driving up the customer lifetime value. • Curated data sets enabling the creation of ML models and built closed loop data pipelines for training the models that are used for consumer segmentation, churn prediction, acquisition strategy, sentiment analysis and optimize paid media spend. • Developed a highly functional Analytics Layer providing users/teams ability to explore data, collaborate, automate workflows, and scale to extract value from all parts of the data lake. • Established enterprise SSO integration, governance principles and centralized Identity and Access Management ensuring the data platform is CCPA, GDPR and SOX compliant.

Led the cloud deployment of enterprise data analytics processes, pipelines, and infrastructure on AWS enabling advanced analytics, ML, and data science implementations. • Modernized on-perm legacy analytical, business intelligence and data engineering efforts resulting in highly performant and efficient data platforms utilizing open source and cloud-based technologies. • Developed customer-centric advanced analytics, user 360 intelligence, and cross-platform customer targeting engine empowering sales, marketing & media planning teams. • Demonstrated effectiveness with attributed measured ROI like sales lift, inventory optimization, acquisition, retention, and consumer engagement across digital platforms. • Deployed an in-house technology platform that integrates 1st and 3rd party data, delivers workflow automation, and enables data-enhanced decisioning for various business units with tools to manage their sales, marketing, and research efforts. • Devised innovations around advanced audience selling are empowering sales and marketing teams to accept new types of demand as well as enhance their existing sales offerings.

Oversaw strategic planning, personnel management, financial oversight, solution deployment and operational performance of large-scale information management and analytical applications across the enterprise. • Managed the architecture, design, development and implementation of the next generation Big Data, Business Intelligence, Data Warehouse and Advanced Analytics environments both in the cloud and on premise enhancing the delivery and efficiency of data products and insights across various business units. • Aligned and directed a broad team of information management professionals. Mentored and developed team resources to create a solid staff infrastructure for activities and future growth.

Created and executed the Enterprise BI and Data Warehouse strategy. Planned, coordinated, directed, and oversaw the design and development activities for all operational phases for corporate Data Acquisition, Data Architecture, Data Integration, ETL, and Reporting/Analytics. • Provided strategic technical thought leadership and mentored team on best practices ensuring deliverables adhered to the requirements and exceeded expectations laid out by organizational stakeholders. • Managed cost, schedule, and quality performance associated with all deployments guaranteeing milestones were met in a timely manner and projects came within budget. • Partnered with and managed vendor relationships for software and consulting services monitoring progress against statement of work and contractual obligations.