WORK
Anique, LLC
Data Consultant Oct 2023 - Apr 2024
- Lead R&D initiatives to develop and implement an advanced, scalable data architecture for a dynamic ecommerce product catalog, ensuring secure and reliable cloud-based database operations
- Establish strategic partnerships with external companies to acquire valuable data sources, facilitating data enrichment for informed business decisions
- Implement AI algorithms for product attribution, search, and filtering to enhance UX and increase customer engagement
Condé Nast
Data Analyst Jun 2022 - Aug 2022
- Built scalable ETL pipelines that support consumer events of the 16+ brands such as Vogue, GQ, WIRED, and The New Yorker for 2M+ customers using Apache Spark, Airflow, S3, and Databricks Delta Tables; enabling real-time data processing, providing visibility into critical metrics, and reducing data latency by 15%
- Applied scripting expertise to securely transfer sensitive information (database credentials, tokens, passwords, certificates, and API keys) to support vendor migration, enhancing data security and mitigating unauthorized access risks
- Leveraged Terraform to automate the provisioning and management of Condé Nast's global data platform, reducing infrastructure deployment time by 20% and providing a robust foundation for data processing and analytics
- Researched and developed a proof of concept for an in-house analytics tool to monitor social media engagement, securing buy-in from senior management (CTO, VP of Marketing, and SVP of Audience Development)
McKinsey & Company
Data Engineer Jul 2021 - Dec 2021
- Developed and implemented an automated recovery processing system in Domo to validate data, analyze usage, and calculate monthly chargeback for 15+ services, reducing manual steps and saving over 50% in ETL time
- Created and deployed a consolidated report visualizer for the finance and operation teams, centralizing critical data, providing real-time updates and ensuring data security and privacy compliance for over 200 employees
- Implemented AI-driven capabilities and leveraged external data sources to optimize a knowledge-aggregation tool for the Client Capabilities Hub, resulting in a 35% reduction in business analysts’ information access time while ensuring data synchronization, CI/CD, and facilitating swift diagnosis and resolution