Chitral Verma is an Enterprise Architect with 9 years of experience designing and shipping data-first platforms that turn telecom and enterprise datasets into privacy-compliant intelligence for AdTech and analytics. He has led architecture and implementation of visual data governance and metadata-driven systems at T-Systems and Deutsche Telekom, and previously built real-time, self-serve streaming platforms and ML tooling on Spark for cloud deployments. An active Apache committer and contributor to projects like Apache Griffin and Polars, he has implemented Delta Lake integration and extended file-format connectors, showing a strong backend systems and data-engineering pedigree. Comfortable moving between hands-on Rust and Spark development and high-level architectural strategy, he focuses on scalable, standardized pipelines that improve data trust and operational decision-making. Based in Pune, he pairs pragmatic product thinking with open-source craftsmanship—he jokes he “hates intros” yet consistently contributes concrete, production-facing improvements to major data projects.
9 years of coding experience
4 years of employment as a software developer
BITS Pilani, Birla Institute of Technology and Science
Bachelor of Technology (B.Tech.), Computer Science and Engineering, Bachelor of Technology (B.Tech.), Computer Science and Engineering at Greater Noida Institute of Technology(GNIOT)
Mathematics and Computer Science, Mathematics and Computer Science at La Martiniere College, Lucknow
Contributions:22 reviews, 50 commits, 17 PRs in 2 years 10 months
Contributions summary:Chitral primarily focused on enhancing the file-based data connector within the Apache Griffin project. Their work involved extending support for various file formats like Parquet, CSV, TSV, and ORC, allowing direct reading from both standalone files and directories. They also introduced the ability to specify schemas directly through options, offering improved flexibility for different file types. Furthermore, the user refactored the configuration of data source connectors and introduced a new profiling measure.
Dataframes powered by a multithreaded, vectorized query engine, written in Rust
Role in this project:
Back-end Developer
Contributions:22 reviews, 5 commits, 10 PRs in 6 months
Contributions summary:Chitral primarily contributed to the Polars project by implementing and fixing features related to Delta Lake integration. Their work included adding support for reading and writing dataframes as Delta tables, along with resolving issues related to Delta lake functionality and improving its usability. The user also addressed a typo, showing a detail-oriented approach to fixing bugs and improving code quality. The commits demonstrate a focus on enhancing the data processing capabilities and integrations within the Polars ecosystem.
polarsdataframespythondataframerust
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Chitral Verma - Enterprise Architect at Deutsche Telekom