$ whoami
frank zhang-zheng
data engineer @ imc trading
kafka · hdfs · kubernetes · sql · java
$ cat highlights.md
I architect and implement high-impact, scalable data solutions — the pipes that move data reliably, and the contracts that keep it trustworthy once it lands.
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streaming
Near real-time ingestion
Pioneered an event-driven framework ingesting high-volume Kafka topics into Snowflake, establishing my organization's first near real-time data processing capability.
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governance
Data Contract framework
Engineered a robust data contract framework, automated its deployment through CI/CD with GitHub Actions, and exposed it via a Python/FastAPI REST API on AWS.
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automation
75% faster account closure
Replaced a manual force-closed accounts workflow with an end-to-end ETL pipeline into Salesforce, cutting the time spent closing accounts by three quarters.
$ cat stack.toml
The tools I reach for, grouped by where they sit in the pipeline.
[languages]
- Python
- SQL
[streaming]
- Apache Kafka
- Event-driven pipelines
[warehouse]
- Snowflake
- Medallion architecture
- ETL / ELT
[cloud]
- AWS Lambda
- DynamoDB
- S3
[services & ci]
- FastAPI
- REST APIs
- GitHub Actions
- CI/CD
[practices]
- Data contracts
- Data quality as code
- Modern data architecture
$ git log --graph --author="frank"
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Data Engineer
- Building low-latency trading data pipelines
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Sr. Data Engineer
- Architected foundational data contract framework
- Pioneered real-time data capability
- Drove major operational efficiency
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Data Engineer
- Built flexible, automated ingestion system
- Implemented data quality as code
- Enabled data science with event-driven pipelines
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Text and Data Mining Engineer
- Developed ETL pipelines using Python and SQL
- Migrated legacy systems to cloud infrastructure
- Optimized query performance, reducing runtime by 60%
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B.S. Physics
$ cat contact.json
Open to interesting data problems. The fastest way to reach me is email.