ClanX

Data Engineer

• Design and build scalable data pipelines and infrastructure that fuel AI and analytics
• Create and maintain data storage solutions including Azure SQL Database, Azure Data Lake, and Azure Blob Storage
• Design, implement, and maintain data pipelines for data ingestion, processing, and transformation in Azure
• Create data models for analytics purposes
• Utilize Azure Data Factory to create and maintain ETL (Extract, Transform, Load) operations
• Implement data validation and cleansing procedures for data integrity
• Ensure data security and compliance
• Collaborate with data engineers and stakeholders to understand requirements and translate them into data platform architectures

Senior Data Engineer – Azure

Backend Engineer

• Develop key platform features such as job scheduling, orchestration, execution engine and resource management
• Write clean, efficient, and well-documented code while adhering to industry standards & best practices
• Investigate and resolve issues in the platform to ensure reliability, scalability and performance
• Work closely with cross-functional teams, including product managers and designers, to contribute to feature definitions and implementation
• Continuously improve your technical skills by working alongside experienced team members and participating in technical discussions

Senior Platform Engineer, Java

Recruitment

• Screening candidates, sharing assignments, and client manager via communication channels
• Reach out to candidates, messaging & maintain follow-up
• Evaluate profiles based on predefined criteria (skills, experience, projects, etc.)
• Maintain and update sourcing trackers regularly
• Schedule interviews with internal stakeholders when needed

Recruitment Intern – Scheduling Ops

• Create and maintain data storage solutions including Azure SQL Database, Azure Data Lake, and Azure Blob Storage
• Design, implement, and maintain data pipelines for data ingestion, processing, and transformation in Azure
• Create data models for analytics purposes
• Utilizing Azure Data Factory or comparable technologies, create and maintain ETL (Extract, Transform, Load) operations
• Use Azure Data Factory and Databricks to assemble large, complex data sets
• Implementing data validation and cleansing procedures to ensure the quality, integrity, and dependability of the data
• Ensure data security and compliance
• Collaborate with data engineers, and other stakeholders to understand requirements and translate them into scalable and reliable data platform architectures

Product Designer

• Own the complete design lifecycle from discovery to final delivery
• Design intuitive and engaging user experiences for B2C products
• Convert product requirements into wireframes, prototypes, and final UI
• Work closely with product and engineering teams on feature planning
• Maintain and improve the product design system
• Use user feedback and data to iterate and improve designs
• Support and mentor junior designers when required

Senior Product Designer

Data Scientist

• Design, build, and productionize data science and AI solutions
• Perform data analysis to generate actionable business insights
• Collaborate with data engineers, software engineers, and AI consultants
• Support client engagements with high-quality analytical deliverables
• Identify AI and automation opportunities for clients
• Contribute to solution design, proposals, and thought leadership

Senior Data Scientist

Customer Success Manager

• Own and manage a portfolio of APAC customers post-sale
• Lead customer onboarding including planning, data readiness, and enablement
• Conduct live product trainings, workshops, and demos
• Partner with customer leaders to define success metrics and track outcomes
• Drive product adoption and identify expansion opportunities
• Act as first-line support for customer questions and issues
• Document, triage, and escalate product issues to Engineering or Product teams
• Coordinate with internal teams to resolve issues and update customers
• Manage customer health, renewals, and risk mitigation
• Maintain accurate customer documentation and success plans
• Explain complex analytics concepts to technical and non-technical users