Greater Bengaluru Area
?
• Spearheaded the transformation of the Enterprise Data Platform, focusing on data governance and integrity of aviation datasets. • Led cross-functional teams of Data Architects, data engineers and machine learning engineers to deliver scalable solutions. • Executed a comprehensive data strategy roadmap, enhancing analytics and operational excellence.
Successfully initiated and deployed a state-of-the-art AWS-based data platform for enterprise use, catering to Innovation, Research, Strategy, Marketing, and Commercial teams. This endeavor resulted in a notable 65% reduction in the time and effort expended by data analysts. Introduced and operationalized data mesh and data lake house platforms, employing the Plan-Build-Run model to ensure a comprehensive and efficient foundation. Provided innovative solutions, including Customer Master and PIMs, Matching Engine, MMS,EDW utilizing advanced NLP and ML algorithms. Facilitated ELT/SLT in visualizing the intricate academic author submission journey, a seemingly daunting task, resulting in significant time savings across 5K+ Journals. Demonstrated senior-level expertise in making decisions on whether to buy or build solutions for enterprise applications. Collaborated closely with key stakeholders, including end users, external and internal producers, architectures, and the PMO, offering detailed milestones and execution plans. Integral to a core leadership team, presented viable options for saving substantial amounts by identifying revenue-generating areas through the optimization of business processes, automation, and data-driven enhancements. Acted as an evangelist in fostering an analytics community of practice, addressing the maturation of data culture and quality across organizations. Implemented diverse initiatives focused on end-user attribution, hyper-personalization, and enhancing marketing experiences through data-centric concepts. Led an international team of over 25 individuals by example, aligning objectives with the overall organizational strategy.
Constructing a Consumer Data Platform, Beyond user paid, Mint data platform at an extensive scale on AWS to deliver insights across Product, Marketing, and Customer Care business units. • Integrating 1 PB of data from 42 million consumers (Online & Desktop) through 100+ Data Pipelines (Batch, Real-time, and 3rd Party). • Ensuring operational excellence through automation via Mobile Alerts, Notifications, Dashboards, and a Self-Healing approach. • Serving as a steward for the Data and Science and AI community across Intuit India.
•Facilitated the advancement of data strategy and capabilities within the Wholesale Data Mart (WDM) Teradata centralized data repository, emphasizing the crucial requirement for accurate, integrated data to fuel insightful reporting and actionable analytics while concurrently mitigating organizational risk. • Operationalized a sustainability initiative, transitioning from a sandbox environment to the data mart. This initiative supported operational and executive reporting of customer data and associated activities, playing a pivotal role in mitigating regulatory and operational risks. • Formulated both logical and physical data models for common dimensions in Teradata Wholesale Data Marts (WDM), including product, internal organization, customer, and time. These models served as the groundwork for ensuring data accuracy and consistency across the data repository. • Executed in-depth data analysis and logical data modeling to fulfill the data requirements of three international groups. This involved a meticulous approach to comprehend and represent the intricacies of the data landscape, catering to diverse business needs. • Provided comprehensive source layer logical and physical models for the Wholesale Integration Hub (iHub), ensuring a structured and well-defined approach to data integration, thereby enhancing efficiency and accuracy in data processing. • Successfully migrated Teradata Data Marts to a Hadoop data lake, optimizing data storage and accessibility. • Implemented data lineage and data governance protocols, enhancing visibility and control over data flow and usage. • Established a data retention policy and archival process, ensuring compliance with data management standards and facilitating efficient data storage practices. • Modelled WDM, wholesale operational risk and compliance (WORC) and profit view data marts