Data Analyst (PySpark, SQL, 30k)

Key responsibilities:

• Owned end-to-end migration of enterprise data platforms to GCP, ensuring accurate, secure transfer of large-scale datasets with minimal operational disruption
• Translated business requirements into actionable data insights, enabling faster and more informed decision-making across multiple business units
• Built and optimised scalable data pipelines using SQL, Python, PySpark, and cloud services to support high-volume data processing and analytics
• Led cross-functional collaboration between data, engineering, and business teams to align requirements, prioritize deliverables, and ensure successful project delivery
• Developed and maintained end-to-end documentation of data workflows and processes to strengthen governance, reproducibility, and long-term maintainability

Candidate profile:

• 1-3 years' experience as a Data Analyst or similar role, with foundational exposure to data engineering and analytics environments
• Proficient in SQL, Python, and PySpark, with hands-on use of cloud platforms (preferably GCP) for data processing and transformation
• Exposure to data migration projects is highly desirable, supporting end-to-end movement and validation of datasets across systems
• Fluent in Cantonese and English, with strong stakeholder communication skills to collaborate effectively across technical and business teams
• Strong analytical and problem-solving skills, with the ability to troubleshoot data issues and deliver practical, scalable solutions

About the company:

A well-established financial services organisation is driving large-scale digital transformation and data innovation initiatives across regional markets. It offers a collaborative, forward-looking environment where employees are empowered to work with modern technologies, contribute to impactful projects, and grow their careers through continuous learning and development.

Keywords: data analysis, data migration, data automation, SQL, Python, PySpark, financial services

What's next:

Apply now to be part of a forward-thinking team driving data transformation and innovation.