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Timothy Wong
Mid-level Data Engineer specializing in experimentation, analytics, and AI-driven product experiences
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About
Built production LLM automations using the Claude API, including a sales enablement workflow that summarizes playbooks and incorporates sales call metadata into strategic one-pagers. Experienced in orchestrating and scheduling data pipelines with SnapLogic, Airflow, and Databricks, and in scaling LLM API calls via parallel/batch processing. Also partnered with HR to deliver prompt-tuned, automated Slack messaging aligned to business tone and acceptance criteria.
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Key Strengths
- Built and deployed LLM workflow to generate sales one-pagers from playbooks and sales call metadata
- Scaled LLM API usage for large call datasets using parallel and batch processing
- Hands-on orchestration across SnapLogic, Airflow, and Databricks scheduling for Python data pipelines
- Prompt tuning to reduce hallucinations and improve summarization precision
- Collaborated with HR stakeholders to define tone/verbiage and acceptance criteria for automated Slack messaging
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“Built and shipped an LLM-powered data quality assistant that generates maintainable validation checks from metadata while executing validations via Great Expectations, exposed through FastAPI and integrated into Airflow-managed pipelines. Emphasizes production reliability (structured outputs, guardrails, monitoring, versioning, human review) and works closely with compliance/operations teams to deliver clear, auditable, user-friendly AI outputs.”
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