Yuanfeng Wang

Designed production ETL/ELT architecture integrating provider rosters, eligibility, transplant, and reference data through incremental database extracts, API connectors, file ingestion, and standardized transformation layers. Developed AWS-based ingestion and storage workflows using S3, Glue, Lambda, and Snowflake, separating raw, validated, and curated datasets for downstream analytics and operat

Engineered cloud data pipelines for healthcare and financial data workflows, combining SQL Server, REST APIs, structured files, and relational sources through Python, SSIS, and Azure Data Factory. Developed reusable Python ingestion components with parameterized endpoints, pagination, incremental extraction, authentication, rate-limit handling, and structured error logging for API-driven integrati

Developed T-SQL stored procedures, views, and functions to transform operational healthcare and financial data into consistent reporting datasets and reusable analytical structures. Built and maintained SSIS packages for scheduled extraction, cleansing, transformation, and loading across relational databases and file-based source systems.

Developed SQL-based data integration workflows for industrial operational systems, consolidating equipment, production, and reference records into structured datasets for analysis. Created Python scripts and scheduled data-processing routines to automate file ingestion, standardize incoming fields, and handle inconsistent source formats.

Assisted with SQL-based extraction and preparation of operational data, organizing source records into consistent structures for internal reporting and analysis. Developed and tested data-cleaning scripts to standardize field formats, identify missing values, and resolve common inconsistencies in source files.

Master's Degree in Engineering/Industrial Management from Rutgers University–New Brunswick from 2013 to 2015.