Lahore, Punjab, Pakistan
Experienced Data Engineer and thought leader in the data space with a strong track record of building modern data platforms, envisioning product features, and driving data strategy—particularly within the fintech domain. At DGlobal, I’ve led the design and deployment of real-time data infrastructure, integrated streaming pipelines, and built a self-serve lakehouse architecture to power analytics at scale and explore how data can unlock intelligent, context-aware experiences in a core banking application. Beyond engineering execution, I’ve played a key role in shaping product features, developing platform roadmaps and in fostering a culture of transparency, accountability and innovation. My experience spans leading agile teams, delivering reliable data systems, and partnering across teams to embed intelligence into financial services. I hold a Master’s in Computer Science from the University of Southern California as a Fulbright scholar. My academic work focused on the applications of machine learning and artificial intelligence, with projects on boosting and curriculum learning in federated models, ML in agroecology, and ethics in AI research. Earlier in my career, I worked at the House of Habib under the mentorship of senior corporate leaders and played a pivotal role in establishing Thal Boshoku Pakistan—a car seat manufacturing facility—while gaining cross-industry exposure in manufacturing, education, and banking.
Leading a team of 4 data engineers to develop robust data pipelines, focusing on scalability, reliability and maintainability.
Designing DGlobal's data architecture in order to best serve the company's mission to transform financial management for everyone.
• Worked on Airlift’s analytics database (Snowflake) pipeline integration with production databases (PostGRES), enabled using Stitch, including ~200+ queries migration from PostgreSQL to SnowSQL. • Ensured data continuity during database segregation activities and handled runtime issues related to queries and gaps in data by identifying possible bugs in CX/Warehouse/Rider apps, query or data sync problems, and transformation logic. • Designed custom ETL solutions using Python to set up data quality and discrepancy checks. • Pioneering MLOps team member, created custom scripts for deploying a Product Recommendation Engine using Python, Prefect and Elasticsearch – integrated with Snowflake and Amazon S3. • Conducted in-depth exploration and hands-on experimentation of Kafka Connect for stream-based integration. • Designed a Customer Churn prediction data model in coordination with the Advanced Analytics team.
Designed experiments for Federated Learning infrastructure to determine performance gain provided by Boosting
Working on identifying Curriculum Learning approaches to integrate with Federated Machine Learning models.