Data Engineer

HKT; Hong Kong; On-site; HKD 520,000 - 760,000; Full time

Job summary

HKT is building a next-generation cloud-based data platform for its Hong Kong operations, seeking skilled data engineers and analysts to enable data-driven decision making through Big Data and live data processing.

You will design and optimize data pipelines on GCP, craft data marts and warehouses, and collaborate with data scientists, BI analysts, and cross-functional teams to deliver reliable, scalable analytics solutions while upholding governance and security standards.

Qualifications

• Bachelor's degree in CS/IT/Data Science or related field.
• 3+ years in data engineering, data warehouse, or BI development.
• 5+ years for Senior Data Engineer / BA with proven delivery and stakeholder-facing experience.
• Hands-on experience in data warehouse/lake design, ETL development, and cloud data platforms (GCP/AWS/Azure).
• Proficiency in SQL, Python, and data visualization tools (Power BI, Tableau, or Looker).
• Fluent in English and Chinese (spoken and written).

Responsibilities

• Design, build, and maintain 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 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.

Skills

Analytical thinking

Communication

Team collaboration

Data quality

Learning agility

Education

Bachelor's degree in Computer Science / Information Technology / Data Science

Tools

SQL

Python

Power BI

Tableau

Looker

RDBMS

NoSQL

GCP / AWS / Azure

Job description

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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