Shazia Samreen

The Artus reader library (~27,000 transitive dependencies) was too large to embed in downstream client applications, causing build failures and blocking a key storage system client's rollout. Analyzed the full dependency tree, identified the top contributors, and refactored them to reduce library size by 40%. Unblocked adoption across hundreds of client applications and resolved company-wide build health issues.

Designed and implemented support for schema-mismatched fields in the Artus columnar reader/writer — a common problem in distributed systems where proto descriptors diverge. For write-time unknowns (field absent from writer schema), data is preserved as serialized blobs instead of columnar shredding. For read-time unknowns, resolution relies on file column datatype metadata. Led the read-path implementation and guided a teammate on write-path. Ensured lossless data integrity during schema evolution, unblocking petabyte-scale migrations from legacy formats.

Initiated and designed a next-generation modular, stateless data transformation library to replace a tightly-coupled, stateful reader. New architecture emphasizes separation of concerns and minimal dependencies, enabling comprehensive unit testing, faster rollouts, and support for large data rows across major data warehousing platforms.

Became key expert for the core data reading stack. Mentored new team members, resolved critical production bugs including high-priority customer escalations and memory issues, maintaining system stability.