Data Engineer - Insurance, Regional, 12 months

Michael Page; Hong Kong; On-site; HKD 260,000 - 420,000; Full time

Job summary

Michael Page is seeking a Data Engineer in Hong Kong for an insurance-focused client with regional exposure. You will design, build, and maintain data pipelines to support reporting, analytics, and operations.

The role covers data modelling, ETL/ELT, MI dashboards, cloud platforms, data governance, and collaboration with business users. Fresh grads welcome; 1–2 years preferred; Power BI/Tableau experience helpful; ML/AI exposure a plus.

Qualifications

• Fresh graduates welcome with internship/project experience.
• 1–2 years of experience in data engineering or related fields preferred.
• Experience in regulated industries is advantageous but not mandatory.
• Proficient in Python and SQL.
• Experience with data visualization tools (Power BI/Tableau/Qlik Sense/Looker Studio).
• Exposure to cloud data platforms (Databricks/AWS/Azure/GCP).
• Understanding of data modelling, ETL/ELT, and data warehousing.

Responsibilities

• Design, develop, and maintain data pipelines for reporting and analytics.
• Assist in data modelling and database development for quality and scalability.
• Perform ETL/ELT from multiple data sources.
• Develop MI reports, dashboards, and visualizations for stakeholders.
• Support cloud-based data platforms and migrations.
• Collaborate with business users, analysts, and tech teams on data needs.
• Assist in data governance, quality monitoring, and documentation.
• Participate in AI/ML initiatives and PoCs where applicable.

Skills

Python

SQL

Data visualization

Data modelling

ETL/ELT

Education

Bachelor's degree in related field

Tools

Power BI

Tableau

Qlik Sense

Looker Studio

Databricks

AWS

Azure

GCP

Job description

• Insurance Company with regional exposure

• Insurance Company with regional exposure
• Data Engineer

About Our Client

Leading insurance group

Job Description

As a Data Engineer, your main responsibilities will include:

• Design, develop, and maintain data pipelines to support reporting, analytics, and operational requirements.
• Assist in data modelling, schema design, and database development to ensure data quality and scalability.
• Perform data extraction, transformation, and loading (ETL/ELT) activities from multiple data sources.
• Develop management information (MI) reports, dashboards, and visualizations for business stakeholders.
• Support cloud-based data platforms and contribute to data migration and transformation initiatives.
• Collaborate with business users, analysts, and technology teams to understand and deliver data requirements.
• Assist in data governance, data quality monitoring, and documentation activities.
• Participate in AI/ML-related initiatives and proof-of-concepts where applicable.

The Successful Applicant

A Successful Data Engineer Should Have

• Fresh graduates with strong academic performance and relevant internship/project experience are welcome.
• 1-2 years of experience in data engineering, data analytics, business intelligence, or related fields is preferred.
• Experience within banking, insurance, financial services, or other regulated industries is advantageous but not mandatory.
• Hands-on programming experience in Python, SQL, or other relevant programming languages.
• Experience with data visualization and dashboard development using tools such as Power BI, Tableau, Qlik Sense, Looker Studio (Data Studio), or similar platforms.
• Exposure to cloud-based data platforms such as Databricks, AWS, Azure, Google Cloud Platform (GCP), or equivalent technologies.
• Understanding of database concepts, data modelling, ETL/ELT processes, and data warehousing principles.
• Knowledge or experience in Machine Learning (ML) and Artificial Intelligence (AI) projects would be an advantage.

What's on Offer

Quote job ref: JN-102026-7121141