Data Engineer

Database operations and optimization: schema design, indexing/partitioning, query tuning, backup/restore, monitoring/alerting, and routine maintenance for databases. Data pipelines: build batch/incremental jobs to ingest R&D data from multiple sources, perform cleaning/standardization, split/route data by rules, and load into curated tables/collections and views. Data modeling and dataset delivery: design subject-area datasets and a lightweight metrics/KPI layer in the database to support analytics and modeling. Data quality and regression: implement validation rules (units/definitions, completeness, consistency, ranges), generate quality reports, and run regression checks for changes in schema/logic. Code-based visualization: build and maintain a small set of high-impact internal dashboards/apps for key R&D metrics and data health. Advanced efficiency: use agent-based automation to accelerate repetitive tasks such as schema mapping, cleaning-rule generation, anomaly triage, documentation/runbook drafts, and QA report generation. Collaboration: work with scientists/engineers to clarify definitions, iterate on data models, and improve data usability.

Strong Python and SQL; able to independently implement reliable data processing/loading jobs and maintain production code. Hands-on experience with at least two of the following: MySQL, PostgreSQL, MongoDB; comfortable with database troubleshooting and performance tuning. Practical experience with ETL/ELT, data modeling, and working with messy real-world R&D/industrial datasets. Engineering fundamentals: job scheduling, logging, monitoring, error handling, version control, and documentation. Preferred： Stream processing or modern data stack exposure (e.g., Kafka, Spark/Flink, Trino/Presto). Streamlit (or similar) app development and basic frontend sense for internal tools. Agent/automation frameworks (e.g., OpenClaw, LangChain, LlamaIndex) used for developer productivity or data workflow automation. Experience with time-series/curve data, lab/test data, or scientific data formats.