Data Engineer
Summary
Builds structured data delivery systems, analytical platforms, and monitoring dashboards for Compliance and Trading teams, plus real-time data collection (web scraping/APIs) and AI data agents. Core stack: Python, Spark/Hadoop, OLAP engines (Presto/Doris/StarRocks/ClickHouse), SQL, with some Java and Docker/Kubernetes.
About the role
This is a Data Engineering role focused on building structured data delivery systems, analytical platforms, and data governance frameworks. You will leverage big data technologies to support Compliance, Trading, and other business teams, develop monitoring dashboards, establish data standards, and build data agents to automate workflows.
Key responsibilities
Leverage big data technologies to build a structured data delivery system for Compliance, Trading, and other business teams; ensure timely, accurate, and traceable data outputs, and maintain the team's existing data development workflows
Develop analytical systems and monitoring dashboards for business teams; produce data reports to support performance attribution and data-driven operational oversight
Author application-layer data warehouse documentation, establish field-level data standards, and lead company-wide data asset management
Build data agents (e.g., MCP Skills) to automate data retrieval and analysis workflows, improving team productivity
Build efficient, real-time data collection systems to scrape or procure the data resources the team needs — including but not limited to web scraping, procured API ingestion, and management of various procured accounts
About you
5+ years of experience in Data Engineering or Data Analyst
Strong Python skills for data analysis and modeling (Pandas, NumPy, Scikit-learn, Matplotlib, PyTorch, TensorFlow); solid coding fundamentals
Proficient with big data frameworks (Spark, Hadoop) and large-scale data processing; familiar with one or more OLAP engines such as Presto / Doris / StarRocks / ClickHouse
Strong SQL skills, capable of complex queries and data modeling independently
Experienced with AI coding tools (e.g., Codex, Claude Code, Kilo Code); able to integrate AI into daily workflows
Familiar with Git and standard version control practices
Working knowledge of Java and mainstream frameworks (e.g., Spring / Spring Boot), and of container-based deployment (Docker / Kubernetes)