Zawar Khan is a data engineer with nine years of hands-on experience building end-to-end data pipelines, predictive models, and production services across cloud and on-prem environments. He has transitioned from data science roles—developing ML classifiers, real-time anomaly detection, and computer-vision solutions—to engineering positions focused on scalable ETL/ELT, API development, and data platform work at Mercury Media Technology. Skilled in Python and familiar with AWS, Kafka, Django and testing frameworks, he also teaches and authored practical workshops on data science and ML tooling. An active open-source contributor, Zawar added functionality and tests to the widely used Airbyte platform by improving its TikTok Marketing connector with configurable end-date support. Based in Norderstedt, Germany, he blends statistical rigor from an applied-mathematics background with pragmatic software engineering to turn data insights into reliable, production-ready systems.
9 years of coding experience
5 years of employment as a software developer
Applied Mathematics For Networks And Data Science, Applied Sciences, Applied Mathematics For Networks And Data Science, Applied Sciences at Hochschule Mittweida (FH)
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at National University of Computer and Emerging Sciences
High School, Science, High School, Science at Beaconhouse
The leading data integration platform for ETL / ELT data pipelines from APIs, databases & files to data warehouses, data lakes & data lakehouses. Both self-hosted and Cloud-hosted.
Role in this project:
Back-end Developer
Contributions:30 reviews, 41 commits, 11 PRs in 9 months
Contributions summary:Zawar contributed to the development of the source-tiktok-marketing connector within the airbyte platform, specifically adding an end date configuration to the connector. They modified source code files, updated specification files, and integrated unit tests to ensure proper functionality and data replication. The user also made updates related to version bumping and formatting.
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