Data Engineer

2 weeks ago

Kuala Lumpur, Kuala Lumpur, Malaysia Prudential Hong Kong Limited Full time

Prudential's purpose is to be partners for every life and protectors for every future. Our purpose encourages everything we do by creating a culture in which diversity is celebrated and inclusion assured, for our people, customers, and partners. We provide a platform for our people to do their best work and make an impact on the business, and we support our people's career ambitions. We pledge to make Prudential a place where you can Connect, Grow, and Succeed.

The Data Engineer is responsible for Extracting, Loading, and Transforming (ELT) data as well as managing the Change Data Capture (CDC) using Qlik Replicate to ingest data into Data Lake, Data Models, Data Marts, and the 7-Sisters Master Data Management platform that helps establish data-driven decision-making across the organization.

This is a new Data Team (Tribe) under the IT Department that will drive the Data Strategy for the organization. They will work with respective Data Owners to develop the data models, data marts, and data analytics for the whole PruBSN organization, following the regional Data COE approach to maintain good data governance and develop the 7-Sisters Master Data Management. The Data Strategy for PruBSN will be executed via the 'Hub & Spoke' approach, with the 'Hub' being this core Data Team under IT, collaborating and working with the respective department Data Stewards and PruBSN Data Heroes (Power BI superusers), i.e., the 'Spokes'.

Key Accountabilities
  1. Serve as the technology evangelist to develop integrated solutions that demonstrate business value.
  2. Work with business stakeholders to understand business priorities and optimize IT strategies to support them. Scope includes full lifecycle, from approach strategy, architecture design, solution development, to installation and deployment.
  3. Design, develop, and implement effective extract, transform, and loading (ETL/ELT) based on data needs along with database solutions and models to store and serve the data accordingly.
  4. Perform assessments/gap analysis of the current technology landscape and identify high-impact areas of improvement.
  5. Collaborate with relevant teams to deliver transformation roadmaps, optimization, and standardization strategies.
  6. Review data mapping, design, and technical documentation.
  7. Lead and enable data team members to gain new skill sets and apply them for deliverables.
  8. Understand and translate business requirements and work on various source systems (IL, DCMS, RCS, BPM, UME, SunGL, etc.) and databases (PostgreSQL, DB2, Oracle, Azure Synapse Analytics, MongoDB, etc.).
Performance Measures
  1. Deliver a Unified Data Platform.
  2. Implement Customer and Contract Master, Product and Pricing Master.
  3. Enable Customer Insight Platform.
  4. Publish and Subscribe Data for Artificial Intelligence / Business Intelligence use cases.
  5. Lead and guide team members to deliver data-related projects on time and on budget.
  6. Ingest, curate, and orchestrate data for data consumers.
  7. Review data mapping, design, and technical documentation.
Qualification and Experience

The Data Engineer should be familiar with data science, business intelligence, and data analytics. He/she should have prior knowledge of data integration, data warehousing, modeling, business intelligence, and presentation concepts.

Required Skills for Data Engineer
  1. Must-Have Experience With Azure Data Tools: A Data Engineer must possess experience working with Azure Data tools e.g., Azure Data Factory, Azure Data Lake, Azure Synapse, and BI systems like Power BI, Tableau, SAP, etc. They must have experience in creating data-rich dashboards, writing DAX expressions, and implementing row-level security in Power BI. Additionally, they should be able to develop custom BI products that require knowledge of scripting languages and programming languages like R and Python.
  2. Required Experience In Data-Specific Roles: A minimum of 2 or 3 years working with ETL tools, or any data-specific roles is required. Candidates are expected to have sound knowledge of database management, SQL querying, data modeling, data warehousing, and OLAP (Online Analytical Processing).
  3. Knowledge In Microsoft BI Stack: Knowledge and experience with Microsoft Business Intelligence stacks such as Power BI, Power Apps, Power Pivot, SSRS, SSIS, and SSAS is an added advantage.
  4. Software Development Skills: While not required to be an expert in software development, a Data Engineer must know how to develop a custom data structure to support BI solutions and Application Programming Interface (API). Understanding technical aspects and software development architecture is essential to transform requirements into technical presence.

Prudential is an equal opportunity employer. We provide equality of opportunity and benefits for all who apply and perform work for our organization irrespective of sex, race, age, ethnic origin, educational, social and cultural background, marital status, pregnancy and maternity, religion or belief, disability, or part-time/fixed-term work, or any other status protected by applicable law. We encourage the same standards from our recruitment and third-party suppliers, taking into account the context of grade, job, and location. We also allow for reasonable adjustments to support people with individual physical or mental health requirements.

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