Data Warehouse Engineer

Bybit is hiring a Data Warehouse Engineer in Kuala Lumpur, Malaysia. Level rates it ; you can apply on Bybit.

Level's read on this job

Works on AI ●●●○ is how Level rates this role: the daily work is on AI products, without building the model.
The posting mentions SQL, Sparksql and Big Data Engines among its tools and skills.
Level classes it as a mid-level role.
Bybit has 152 other open roles on Level.

AI in this role

Build and optimize data warehouses, tagging systems, and feature engineering to support personalized recommendations and intelligent applications.

SQLSparksqlBig Data Engines

data-warehousefeature-engineeringdata-governancesql-optimizationdata-modeling

About Us

Established in 2018, Bybit is one of the world’s leading cryptocurrency exchanges and digital financial platforms, serving over 80 million users across more than 200 countries and regions. Powered by world-class technology and a user-first mindset, Bybit delivers a seamless ecosystem across trading, payments, wealth management, custody, institutional services, and Web3 — connecting users to the future of digital finance. Our core values define how we build. We listen, care and improve to create products and experiences that put users first. Backed by a global team of ambitious builders, problem-solvers, and innovators, we foster a high-performance and fast-moving environment where talent is empowered to drive real impact at the global scale. Supported by 24/7 multilingual customer service and a strong commitment to innovation, we are shaping the future of finance through technology, collaboration, and bold execution. Today, Bybit is recognized as one of the most trusted and transparent platforms in the digital asset industry, continuing to expand its global presence while building the infrastructure for the next generation of financial services.

Job Responsibilities

Warehouse Construction & Optimization: Responsible for the construction and optimization of the group-level public data warehouse (Offline & Real-time) to consolidate unified data assets.
Tag System Development: Lead the construction of the tag system, developing both real-time and offline tagging capabilities to support business activities and precision user outreach.
Feature Engineering: Design and develop user and product feature libraries; collaborate with algorithm teams to drive the implementation of personalized recommendations and intelligent applications.
Modeling & Architecture: Gain a deep understanding of business requirements to complete data warehouse modeling and data asset design, ensuring the reusability and scalability of platform data.
Data Governance: Establish systems for data cleaning, quality monitoring, and alerting to continuously improve the accuracy and stability of data delivery.

Job Requirements

Education: Bachelor’s degree or above in Computer Science, Mathematics, Statistics, or related fields.
Technical Experience: At least 2 years of experience in data warehouse development. Expert proficiency in SQL with extensive experience in SQL optimization and familiarity with big data engines such as SparkSQL.
Core Knowledge: Deep understanding of Data Warehouse and BI systems, including ETL, data warehouse architecture, OLAP, and multidimensional modeling.
Programming Skills: Proficiency in at least one programming language among Python, Scala, or Java, with strong engineering capabilities.
Ecosystem Familiarity: Preferred experience with the big data ecosystem, including Hadoop, Hive, Spark, Flink, Kafka, Trino, Doris, or TiDB.
Soft Skills: Rigorous work ethic, excellent logical thinking and learning abilities. Skilled in communication and teamwork with the ability to independently drive the resolution of complex issue.

Why Join Us
At Bybit, we are committed to fostering a supportive and enriching work environment.
Our benefits include:
- Study Growth Fund: We support your professional development and continuous learning.
- Internal Events: Participate in regular team-building activities, workshops, and events designed to promote collaboration and innovation.
- Global Collaboration: Be part of a diverse, international team, working alongside colleagues from around the world.
- Career Advancement: Access opportunities for growth and advancement within a rapidly expanding global company.
- Internal Mobility: Grow with us- Your long-term development is important to us. We offer internal job opportunities to help build your career path.

How we rate this

Data Warehouse Engineer at Bybit rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Data Warehouse Engineer is an open job at Bybit.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in Kuala Lumpur, Malaysia.
The job was posted on May 14, 2026.
Seniority: mid.
Applications are handled by Bybit. Apply on Bybit

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Data WarehouseFeature EngineeringData GovernanceSQL OptimizationData ModelingSQLSparksqlBig Data Engines

Questions you could be asked

Tell me about a project where data warehouse was part of your work. What did you do?
Tell me about a project where feature engineering was part of your work. What did you do?
Tell me about a project where data governance was part of your work. What did you do?
Tell me about a project where sql optimization was part of your work. What did you do?
Tell me about a project where data modeling was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Data Warehouse, Feature Engineering, Data Governance, SQL Optimization, and Data Modeling. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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