I build and operate production data infrastructure for ESG and Government Climate products, focusing on system integration, validation, and reliability under real-world constraints.
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Own production pipelines generating ESG and climate scores across thousands of entities, with strict correctness, auditability, and SLA requirements.
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Designed and built automated validation and replay frameworks that reprocess real production artifacts across environments, reducing feedback loops from days to minutes.
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Built parameter ingestion and synchronization pipelines across Dev, Beta, and Prod with human-in-the-loop approval, diffs, and full audit trails.
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Unified fragmented workflows across Research, Product, and Engineering by designing clear interfaces and integration boundaries for complex domain logic.
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Led modernization of large legacy Python systems (350k+ LOC), upgrading runtimes and dependencies while improving CI safeguards and release discipline.
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Developed internal tooling and dashboards that replaced manual data inspection, improving transparency and reducing validation time from days to under an hour.
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Act as the technical bridge between complex domain logic and production systems, enabling stakeholders to reason about edge cases, tradeoffs, and failure modes during releases.
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Present internally on scalable testing, validation, and reliability for complex data pipelines.
Built and maintained internal platforms supporting ESG analytics, metadata management, and client-facing data products.
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Led refactors that simplified complex codebases, improved developer velocity by 3×, and aligned implementations with modern engineering best practices.
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Collaborated closely with Product, UX, and Data teams to deliver features end-to-end, from requirements through production rollout.
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Actively contributed to mentoring, interviewing, and internal engineering initiatives.
