Data Engineering Professional | Pipeline Architect | Medical Device Systems | Google Developer
Data Engineer specializing in the design and implementation of reliable data pipelines and backend architectures for high-stakes industries (MedTech/Pharma). Expertise in architecting Python-based ETL processes, managing complex datasets (DICOM), and building robust software tools that ensure data flow and system integrity. Focused on bridging the gap between specialized domain data and scalable, modern data engineering infrastructures.
Data Engineering - ETL/ELT pipeline design, data modeling, high-throughput ingestion, and automated data movement
Software Engineering - High-performance Python, backend tool development, concurrency (Asyncio), and architectural patterns
Data Infrastructure - Containerization (Docker), CI/CD automation, and cloud-native data deployments
Data Integrity & Reliability - Systematic performance telemetry, automated data verification, and root-cause analysis for mission-critical datasets
Technical Strategy - Requirements-to-pipeline translation, cross-functional data alignment, and technical project leadership
Data Systems & Imaging Pipelines
- Developed a suite of 15+ Python-based data processing and diagnostic tools, utilizing concurrent processing to optimize system calibration data analysis workflows.
- Engineered automated data verification pipelines for software/hardware interfaces, resolving 45+ critical data-flow issues within imaging systems.
- Designed and maintained scalable data infrastructure ensuring high reliability and integrity for specialized veterinary and orthopedic imaging datasets.
- Created modular data visualization and telemetry tools to monitor system performance and data throughput for cross-functional engineering teams.
Data Integration & Manufacturing Pipelines
- Designed and deployed end-to-end data automation solutions for pharmaceutical manufacturing, focusing on reliable data ingestion from legacy systems into modern architectures.
- Managed the technical lifecycle of the InfoLog product suite, implementing five architectural updates to improve data ingestion performance with zero production downtime.
- Architected robust data pipelines ensuring high availability, auditability, and integrity for mission-critical manufacturing records.
- Led technical integration projects for enterprise customers, optimizing data interoperability and schema mapping across heterogeneous data environments.
Process Engineering & Data Analysis
- Engineered automated production systems, ensuring precise data synchronization between hardware controllers and monitoring software.
- Authored 30+ technical protocols to certify system and data performance against stringent industry and regulatory standards.
- Analyzed production datasets using statistical methods to identify throughput bottlenecks and optimize manufacturing data flows.
- ETL Architecture: Experience building ingestion and processing scripts for complex, multi-modal datasets (DICOM, sensor logs).
- Pipeline Reliability: Strong focus on building fault-tolerant data movement systems that ensure 100% data auditability and integrity.
- Performance Engineering: Developing backend tools that analyze and optimize system behavior for maximum data throughput.
Programming Languages: Python, SQL, C#, automation scripting
Data Engineering & Infrastructure: Docker, Jenkins, GitHub Actions, ETL Design, Schema Mapping
Project Management: Agile methodologies, requirements analysis, technical documentation
Data Standards: DICOM, 21 CFR Part 11, Data Integrity Frameworks
System Analysis: Performance telemetry, root-cause analysis, statistical process control
Geographic Experience: Shenzhen, China | Atlanta & Baltimore, USA | Oxford, UK
Cross-Cultural Engineering: International project delivery and regulatory compliance experience
Email: amalie.shi.jhmi@gmail.com
LinkedIn: linkedin.com/in/amalieshi
Google Developer: g.dev/amalieshi
Portfolio: https://amalieshi.github.io/
Committed to delivering high-quality engineering solutions through systematic approaches to problem-solving, rigorous testing methodologies, and adherence to industry best practices. Focus on continuous improvement and technical excellence in complex, regulated environments.
