Data Engineer

Bybit; Kuala Lumpur; On-site; MYR 90,000 - 150,000; Full time

Job summary

Bybit in Malaysia is seeking a seasoned Data Engineer/Data Analyst to build scalable data systems for Compliance and Trading teams. You will develop analytics dashboards, automate data workflows, and contribute to data asset governance.

The role emphasizes Python, SQL, and big data frameworks; you will work across data sourcing, data agent development, and real-time data collection, focusing on reliable, reproducible outputs.

Qualifications

• 5+ years of experience in Data Engineering or Data Analyst.
• Fluent in Mandarin and English.
• Strong Python skills for data analysis and modeling; solid coding fundamentals.
• Proficient with big data frameworks (Spark, Hadoop) and large-scale data processing; familiar with OLAP engines (Presto / Doris / StarRocks / ClickHouse).
• Strong SQL skills; capable of complex queries and data modeling independently.
• Experience with AI coding tools and integrating AI into workflows; familiar with Git.
• Working knowledge of Java and Spring Boot; experience with container deployment (Docker / Kubernetes).

Responsibilities

• Routine Data Support: Build a structured data delivery system for Compliance, Trading, and other teams; ensure timely, accurate, traceable outputs.
• Analytics System Development: Create analytical systems and dashboards; produce data reports for performance attribution and oversight.
• Data Asset Governance: Write data warehouse docs, set field standards, lead company-wide data asset management.
• Data Agent Development: Build data agents to automate data retrieval and analysis workflows.
• Data Sourcing & Procurement: Create real-time data collection systems; manage web scraping, API ingestion, and procured accounts.

Skills

Fluent Mandarin and English

Tools

Python

SQL

Spark

Hadoop

Presto / Doris / StarRocks / ClickHouse

Git

Docker

Kubernetes

Java

Spring Boot

TensorFlow / PyTorch

Job description

• 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.