- Implement Customer Data Platform on GCP which is an enterprise-level product including Big Data pipeline, data governance and Machine Learning system.
A. Architecture for High-Throughput Low-Latency Big Data Pipeline on Cloud (ref1)
B. Data Governance (ref2)
C. Hidden Technical Debt in Machine Learning Systems (ref3)
D. The ML Test Score: A Rubric for ML Production Readiness and Technical Debt Reduction (ref4)
- Lead software engineering including architecture design, database design, infrastructure selection and programing language selection.
- Participate in design reviews, code reviews and recommend improvements.
- Improve the maintainability of existing applications.
- Analyze and troubleshoot application issues.
- Collaborate with product, design, and development teams to find innovative solutions to problems.
- Improve the quality of applications under test.
- Train or mentor other engineers when needed.
- Expertise in the software development lifecycle process, including analysis and design, APIs, development tools and technologies, release and version control and deployment management.
- Familiar with at least one programming language (Golang/Java/Python…etc).
- Familiar with at least one cloud-native development (GCP/AWS/Azure…).
- Strong understanding of database design and experience with RDBMS and NOSQL databases.
- Strong understanding distributed system, including latency, consistency, throughput, security, authn/authz issues.
- Familiar with analysis, tracing and monitoring tools.
- Familiar with software testing methodologies.
- Passionate to share knowledge to other engineers.
- Familiar with internet protocol (TCP/IP).
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