Abdullah Shoukat is a Senior Data Engineer with 5 years of experience building scalable data platforms and ML-ready pipelines for global organizations, currently leading a cross-country data architecture effort at Telenor. He combines cloud expertise across Azure and AWS with modern data stack tools—DBT, Spark, Delta Lake, Kafka, Airflow, and Terraform—to process millions of records daily and power real-time executive BI. Abdullah also bridges research and production: he contributed backend and linear-algebra improvements to the Ivy project to help transpile ML code between frameworks, and has built context-aware generative AI data products using LLMs. Known for pragmatic migrations of legacy workflows and rigorous data quality practices (dbt tests, Great Expectations), he excels at aligning engineering, analytics, and business stakeholders to deliver reliable, high-performance data solutions.
5 years of coding experience
5 years of employment as a software developer
Bachelor of Science - BS, Computer Science, A-, Bachelor of Science - BS, Computer Science, A- at University of the Punjab
Intermediate, Pre-Engineering, A-, Intermediate, Pre-Engineering, A- at Punjab group of colleges
Contributions:108 reviews, 94 PRs, 36 pushes in 10 months
Contributions summary:Abdullah contributed to the codebase by adding several functions and tests to support the conversion of machine learning code between frameworks. Their work included implementing the `indices`, `multi_dot`, and `fill_diagonal` functions, along with associated tests. They also refactored numpy indexing routine functions to their respective frontends, and fixed some test cases. The user is focused on improving the functionality and testing of the Ivy library, particularly in the areas of linear algebra and array manipulation.
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