Abu Dhabi Emirate, United Arab Emirates
I’m a Quantitative Researcher & Developer at the Abu Dhabi Investment Authority (ADIA) with a Master’s in Computer Science and Engineering. My background combines software engineering, data science, and quantitative finance, enabling me to design scalable, high-performance systems for data-driven research and trading. I specialize in building high-performance data pipelines, quantitative research tools, and automated analytics frameworks that support systematic strategies. These systems power decision-making across research and production environments. My focus is on delivering robust, efficient, and maintainable systems where precision and performance are critical. I’m passionate about scalable data infrastructure, quantitative modeling, and efficient software systems — from data ingestion to production-grade quant infrastructure. Core Skills: Python, Rust, Docker, Kubernetes, CI/CD, Prometheus, Grafana, AWS, Pandas, NumPy, Polars, NATS, ClickHouse, PostgreSQL and Aerospike. Interested to learn more about me? Drop me an email at [email protected]
• Designed and implemented a data virtualization layer composed of microservices delivering real-time, in-memory analytics enabling low-latency access to multi-asset datasets. • Built a unified symbol mapping system that resolves 200+ entity identifiers in 25+ financial and digital asset data sources, standardizing entity resolution across the research stack. Tech stack: Python 3 · CI/CD · Kubernetes · Docker · ClickHouse · Aerospike · Grafana · Prometheus · NATS.io · gRPC · Protobuf · JSON.
• Developed a global insider transaction data pipeline spanning 60+ jurisdictions delivering point-in-time precision and millisecond responsiveness through event-driven architecture and real-time observability. • Institutional clients point of contact for the usage of insider transaction data and proprietary models. Tech stack: Python 3 · PostgresSQL · Microsoft SQL Server · Docker · NATS.io · Grafana · Prometheus.
• Lectured Information Systems and Databases course to 3 Engineering M.Sc.’s. • Responsible by 4 classes of 1.5H plus 3H of office hours per week, with ∼30 students each • Graded 120+ students having evaluated projects and exams.