全职 Data Engineer 工作, 薪水, Bybit Federal Territory 公司招聘中 - Ricebowl

Responsibilities

• Routine Data Support: 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.
• Analytics System Development: Develop analytical systems and monitoring dashboards for business teams; produce data reports to support performance attribution and data-driven operational oversight.
• Data Asset Governance: Author application-layer data warehouse documentation, establish field-level data standards, and lead company-wide data asset management.
• Data Agent Development: Build data agents (e.g., MCP Skills) to automate data retrieval and analysis workflows, improving team productivity.
• Data Sourcing & Procurement: 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.

Requirements

• 5+ years of experience in Data Engineering or Data Analyst
• Must be fluent In Mandarin and English
• 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 — and not just "vibe coding."
• 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).

Preferred

• GitHub open-source contributions (self-written or AI-assisted both acceptable; any domain: scrapers, full-stack, tooling, etc.).
• Experience building autonomous agents — LLM-based automation, conversational systems, MCP Servers, etc.
• Practical experience in machine learning, deep learning, time-series modeling, anomaly detection, etc.