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Data Engineer - Insurance

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Onsite

Data Engineer - Insurance

Ikas International (Asia) Limited

Data Engineer - Insurance

Skills

SQL QueriesData EngineeringDatabricksGitData AnalysisPySparkAzure

19 days ago

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Important information


Contract type:

Permanent

Salary:

HK$420,000 – HK$540,000 / year

Location:

Hong Kong

Work mode:

Onsite

Published on:

7 October 2026

What they need


Our client is a well-established organisation undertaking a major data transformation initiative and is looking for an experienced Data Engineer to join their growing data team.

Key Responsibilities

  • Design, develop, and maintain scalable data pipelines and data integration solutions across multiple business platforms.
  • Build and optimise data warehouse and analytics environments to support reporting and business intelligence requirements.
  • Collaborate with stakeholders, analysts, and developers to ensure high-quality, reliable, and accessible data assets.
  • Integrate and transform data from legacy and modern systems, enabling seamless data flow across the organisation.
  • Support the continuous improvement of data platform performance, governance, and best practices.
  • Contribute to Agile delivery processes and participate in automation, deployment, and DevOps initiatives.

Requirements

  • Degree in Computer Science, Information Technology, Engineering, or a related field.

  • Minimum 5 years of experience in data engineering, ETL development, or data warehousing environments.

  • Proven hands-on experience working with Azure Databricks, Apache Spark, and PySpark.

  • Strong expertise in SQL development, query optimisation, and database performance tuning.

  • Experience working with Azure SQL Managed Instance or similar cloud-based database platforms.

  • Familiarity with Azure Data Factory, Azure Data Lake, and broader Azure data ecosystem services.

  • Hands-on experience supporting BI and analytics platforms such as Qlik Sense and/or QlikView.

  • Solid understanding of dimensional data modelling, data warehousing principles, and data architecture best practices.

  • Experience using source control tools, CI/CD practices, and Agile delivery methodologies.

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