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Shuju Sun
Mid-Level Software Engineer specializing in real-time data pipelines and ML deployment
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Ticketmaster data engineer who built CDC-driven Kafka pipelines feeding Snowflake for analytics and data science teams. Hands-on in production operations—scaled Kafka during sudden playoff-driven transaction spikes and improved monitoring for preemptive scaling. Known for using small-batch experiments and quantitative metrics to align stakeholders and drive cost-saving architecture changes (e.g., buffering to reduce AWS Lambda invocation frequency).
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Key Strengths
- Built and deployed end-to-end data platform moving backend data through pipelines into Snowflake for analytics/data science consumers
- Requirements alignment via data standardization and data contracts with upstream and downstream stakeholders
- Data-driven conflict resolution: validated a Kafka consumer buffering approach with a small-batch test and quantitative cost-savings metrics
- Production incident response and scaling: mitigated Kafka overload during playoff traffic spikes by pausing non-essential jobs, increasing partitions, and tuning configs
- Proactive monitoring improvements to detect volume spikes earlier and enable preemptive scaling
- Balances rapid prototyping with production hardening (refactor, tests, error handling, interfaces, linting, CI)
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