- Spearhead the design and implementation of deterministic encryption/decryption for client-sensitive data, carefully balancing methodologies to integrate this feature seamlessly into existing workflows, and preparing transition guides for legacy data.- Develop and manage 200+ data pipeline jobs and sensors in Dagster, aligning with complex data dependencies to drive client success; contribute extensively to development logs and documentation to streamline team processes.- Design and build the ML pipeline for a PoC project, enabling frequent, automated experiments tailored to complex customer scenarios, utilizing tools like dbt, Dagster, and Bazel.- Enhance team productivity by optimizing CI processes across the organization, minimizing unexpected Python lint changes, and significantly increasing linter speed in VS Code; concurrently, refactor and remove 10+ unused configuration-related code in the monorepo to uphold code quality and maintainability.- Lead a Design Patterns workshop for engineers to foster a culture of continuous learning, improve engineering capabilities, and build a strong technical community within the company.

- Designed and started to write the feature design document inside the engineer team to help the team members understand the new feature, and setup a better develop practice.- Developed the RESTful API with Django, Postgres, Redis, and AWS stack (Including EC2, S3, RDS, ElastiCache, Lambda function, Route 53) for our data service, and dockerized the system with Docker. Through applying ElastiCache and Redis, successfully sped up 80\% of the API response.- Designed and built up company data infrastructure for satellite data ingestion and preprocess (ETL pipeline) with Airflow, automatically ingested the latest satellite data into our datalake everyday and transformed them into the format that data scientist team needs.- Designed and built up the machine learning pipeline system for continuous evaluation, and deployed the model through API service. Cooperated with data scientist team to integrate their preprocess procedure and machine learning algorithm into the pipeline system, and mentored the interns in programming methodologies and best practices. Eventually built up the API with Flask.- Analyzed satellite data and weather forecast data to locate the candidate area for agriculture product.