Job Description
37 days ago
• **Salary HKD 60,000 - 70,000 x 13 months + discretionary bonus***
Role:
• Contribute to the development and maintenance of data pipelines to onboard and process data from multiple sources.
• Define and standardise data assets, to guarantee high-quality data delivery.
• Support the design and development of scalable data architectures.
• Ensure data quality, reliability, and security by adhering to Data Governance rules and processes.
• As a subject matter expert, continually evaluate and integrate new tools and technologies.
Requirements:
• 4-8 years of experience working with large-scale data platforms and related technologies.
• Expertise in SQL and Python / Scala.
• Hands-on experience using big data tools (Databricks / Spark), SQL and NonSQL databases.
• Direct experience MSFT Azure preferred, other cloud platforms can be considered.
• Bachelor’s or Master’s degree, in Information Technology, Data Science, Computer Science, Mathematics or other technical discipline.
• Good understanding of data modeling techniques and data product implementation.
• Fluency in English, oral and written, is essential.
Role:
• Contribute to the development and maintenance of data pipelines to onboard and process data from multiple sources.
• Define and standardise data assets, to guarantee high-quality data delivery.
• Support the design and development of scalable data architectures.
• Ensure data quality, reliability, and security by adhering to Data Governance rules and processes.
• As a subject matter expert, continually evaluate and integrate new tools and technologies.
Requirements:
• 4-8 years of experience working with large-scale data platforms and related technologies.
• Expertise in SQL and Python / Scala.
• Hands-on experience using big data tools (Databricks / Spark), SQL and NonSQL databases.
• Direct experience MSFT Azure preferred, other cloud platforms can be considered.
• Bachelor’s or Master’s degree, in Information Technology, Data Science, Computer Science, Mathematics or other technical discipline.
• Good understanding of data modeling techniques and data product implementation.
• Fluency in English, oral and written, is essential.
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