Data Engineer

We are seeking passionate and skilled professionals to join our team in building a next-generation cloud-based data platform for one of the largest telecommunications companies in Hong Kong. This platform is a core initiative in the company's transformation toward becoming a data-driven enterprise, leveraging cutting-edge technologies such as Big Data, Cloud computing, event-driven architecture, live data streaming, and advanced data governance frameworks.

Candidates will play a key role in data solution development, analytics enablement, and business insights delivery, collaborating closely with Data Scientists, BI Analysts, and cross-functional stakeholders across the organization.

Key Responsibilities

• Design, build, and maintain robust data pipelines ingesting and transforming large volumes of data into Google Cloud Platform (GCP).
• Develop and optimize data marts and data warehouse structures to support Business Intelligence (BI) and analytical workloads.
• Conduct feature engineering and data preparation for advanced analytics and machine learning models.
• Implement software components following architectural standards, security practices, and coding guidelines.
• Conduct unit testing, support system and user acceptance testing, and assist with production implementation.
• Develop and maintain comprehensive documentation for systems, operations, and data flows.
• Provide ongoing user and application support, ensuring reliability and performance of production data environments.

Business Analysis & Data Governance

• Translate business requirements into clear technical specifications, working closely with business units and IT teams.
• Perform data analysis, gap assessments, and process mapping to identify improvement opportunities.
• Partner with stakeholders to define KPIs, reporting requirements, and analytical frameworks supporting business decision-making.
• Support and execute data governance initiatives, including metadata management, data quality monitoring, and compliance alignment.
• Facilitate effective communication between business and technical teams, ensuring alignment on objectives, priorities, and deliverables.
• Lead and manage data engineering projects across diverse industry sectors (Public, Enterprise, BFSI).
• Drive project planning and execution for data pipeline and data management initiatives.
• Mentor and guide junior data engineers and analysts to achieve project and professional goals.
• Collaborate with stakeholders to ensure project deliverables meet business, technical, and compliance requirements.

Qualifications and Experience

• Bachelor's degree in Computer Science, Information Technology, Data Science, or related disciplines.
• Data Engineer: Minimum 3 years of experience in data engineering, data warehouse, or BI development.
• Senior Data Engineer / Business Analyst: Minimum 5 years of experience with proven technical delivery and stakeholder-facing experience.
• Hands-on experience in data warehouse/lake design, ETL development, and cloud data platforms (preferably GCP, AWS, or Azure).
• Proficiency in SQL, Python, and other relevant programming or scripting languages.
• Good understanding of RDBMS, NoSQL, and data visualization tools (e.g., Power BI, Tableau, or Looker).
• Familiarity with Big Data frameworks, Cloud-native technologies, and Data-as-a-Service (DaaS) platforms is a strong advantage.
• Demonstrated analytical thinking with the ability to interpret complex business problems and convert them into actionable data solutions.
• Excellent communication, documentation, and interpersonal skills; fluent in English and Chinese (spoken and written).
• Project management experience or certifications (e.g., PRINCE2, PMP, or Scrum Master) are advantageous but not essential.

Ideal Candidate Attributes

• Strong analytical and problem-solving mindset with attention to data quality and integrity.
• Collaborative team player with a proactive \"can-do\" attitude.
• Fast learner who embraces new technologies and continuous improvement.
• Comfortable working in dynamic, fast-paced environments under agile methodologies.

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