• Led a team of 10+ data engineers (onshore and offshore) to build an in-house enterprise level reporting solution leveraging various Microsoft Azure Services such as Azure Data Factory, Azure Function App, Azure Logic App, Azure Databricks, Azure Storage Account, etc.• Managed migration of data from legacy data platforms such as on-premise SQL server to cloud based infrastructure, which reduced company’s tech and maintenance cost and enabled scalability.• Created requirements and technical product documentation; designed wireframes for user interface (UI) based on requirements and feedback collected from users.• Manage development cycle of a .NET web application that allow users to easily push or pull data from back-end databases. Deployed a validation process to minimize user errors while uploading data into databases.• Designed and Implemented applications to connect various web services using API calls and/or event subscriptions which helped to streamline ETL pipelines and reduce data latency.• Created processes for automating data quality control to improve data cleanliness and readiness.• Onboarded 10+ clients to the new platform and provide training and ongoing support.

• Implemented standard processes and templates to scale MMM paid media ETL pipelines using JIRA & Confluence. The new framework and processes reduced waste by more than 50%. Trained a team of data consultants to better understand advertising data from various ad-tech vendors.• Conducted client data discovery meetings for understanding business questions to be able to properly identify data requirements and ensure best practice, efficiency and data hygiene.

• Led the design, development and onboarding of 15 clients onto a custom built Datorama reporting solution that was implemented to automate reporting, and improve campaign management and data quality processes. This solution greatly reduced manual labor and human error associated with report generation.• Developed a templatized solution that was able to be deployed across clients at scale, while also allowing for change management, maintenance and centralization.• Datorama Certified Administrator.

• Built process for cross-agency digital advertising benchmarking. Led data acquisition, transformation and visualization of the project. The visualizations and reports provide C-Suite executives an overview of digital investment for all GroupM agencies. This platform also provided agency investment leads the ability to compare rates among suppliers and negotiate for better rates to drive efficiencies across all of GroupM.• Led and trained both onshore and offshore team members to provide ongoing support and maintenance of benchmarking platform. Managed a team of 4 engineers and worked with stakeholders across Digital Investment, Ad-Operations, Analytics and Agency Leadership.

• Built modeling solutions to optimize advertising spend for multiple Fortune 500 brands by integrating disparate data sources and analyzing internal and external factors.• Managed SQL databases and built ETL Pipelines to transform various advertising data sources, such as PRISMA, GCM, Sizmek, AdWords, Google Analytics, Nielsen, DDS, Facebook, Twitter, LinkedIn, etc. • Built client-facing Tableau dashboards that facilitated business understanding, insights and decision making through clear visualizations and narratives. Also handled Tableau Server admin task, manage user access with row-level security.

• Performed ETL to normalize large-scale data using T-SQL to streamline the delivery of cleansed, structured datasets for advanced Marketing Mix Models (MMM).• Built statistical models for one of the world's largest spirits and beverage brands. Determined the effectiveness and efficiency (ROI) of the paid media activities allowing for the brand teams and agency to optimize media investment strategy to drive sales growth.

• Performed pricing elasticity analysis focused on consumers’ reactions to changes in everyday price and the responsiveness of consumers to promotional support. Helped the clients optimize its pricing strategy to support their business goal of increasing YoY sales revenue by 5%.• Used T-SQL to validate large raw data sets, cleansed and categorized data according to modeling needs.