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Senior Data Engineer Job Opening In Kampung Haji Abdullah HUKum – Now Hiring FWD Life Insurance Corporation


Job description

About FWD Group

FWD Group (1828.HK) is a pan-Asian life and health insurance business that serves approximately 34 million customers across 10 markets, including BRI Life in Indonesia.

FWD’s customer-led and tech-enabled approach aims to deliver innovative propositions, easy-to-understand products and a simpler insurance experience.

Established in 2013, the company operates in some of the fastest-growing insurance markets in the world with a vision of changing the way people feel about insurance.

FWD Group is listed on the main board of the Hong Kong Stock Exchange under the stock code 1828.

For more information, please visit

FWD Technology and Innovation Malaysia Sdn.

Bhd., known as FWD TIM, was established in late 2019.

Strategically located in Kuala Lumpur, FWD TIM serves as a pivotal shared service location within FWD Group, providing services to multiple markets across the Group.

FWD TIM houses a diverse and talented workforce focused on essential business and technology services such as information security, cloud operations, IT solutions delivery, digital and data, actuarial, finance, investments, and customer service, among many others.

FWD TIM is dedicated to drive and deliver operational excellence and efficiency, foster innovation and ensure regulatory compliance across all business functions as well as maintain a competitive edge in the market.

PURPOSE

  • A role to be responsible for system design, development and implementation of regional frontend systems.

    Provide maintenance and support on production systems.

  • KEY ACCOUNTABILITIES

  • Design, develop, document and implement end-to-end data pipelines and data integration processes, both batch and real-time.

    This include data analysis, data profiling, data cleansing, data lineage, data mapping, data transformation, developing ETL / ELT jobs and workflows, and deployment of data solutions.

  • Monitor, recommend, develop and implement ways to improve data quality including reliability, efficiency and cleanliness, and to optimize and fine-tune ETL / ELT processes.

  • Recommend, execute and deliver best practices in data management and data lifecycle processes, including modular development of ETL / ELT processes, coding and configuration standards, error handling and notification standards, auditing standards, and data archival standards.

  • Prepare test data, assist to create and execute test plans, test cases and test scripts.

  • Collaborate with Data Architect, Data Modeler, IT team members, SMEs, vendors and internal business stakeholders, to understand data needs, gather requirements and implement data solutions to deliver business goals.

  • BAU support for any data issues and change requests, document all investigations, findings, recommendations and resolutions.

  • KEY PERFORMANCE INDICATORS

  • Maturity level on technical skillsets of management and development on big data platform including data modeling design, data transformation, big data programming and performance tuning

  • Effectiveness of project contribution, including from technical support, project management and team collaboration perspective, to deliver data lake system on assigned local countries

  • Level of understanding on business requirements and capability to transform them into technical solution

  • Variety of new technologies (such as Azure and AWS Big Data Solution, Power BI, Tableau, Python and etc) and techniques being learnt that can be applied to solution delivery

  • EXTERNAL & INTERNAL CONTACTS

  • Group Infrastructure Team, Security Teams and Operation Team

  • Group Project Team

  • Local country Project Team (IT and User)

  • IT Vendors and/or Service Providers

  • QUALIFICATIONS / EXPERIENCE

  • Bachelor in IT, Computer Science or Engineering.

  • At least 3-5 years of using Big Data technologies like Azure and AWS Big Data Solution, Hadoop, Hive, HBase, Spark, Sqoop, Kafka and Spark Streaming.

  • Minimum 5 years of professional experience in data warehouse, operational data store, and large scale data architecture implementations in Unix or/and Windows environment.

  • At least 3+ years of solid hands-on development experience with ETL development to transform complex data structure in multiple data sources environment.

  • At least 5 years data model (relational and/or data warehouse), data mart design and implementation.

  • Minimum 3-5 years ETL programming in any of these languages including Python, Scala, Java or R

  • Experience on Azure Databricks for ETL/ELT development and big data analytics programming in Python

  • Strong Experience with various of ETL/ELT frameworks, data warehousing concepts, data management framework and data lifecycle processes.

  • Solid understanding on Azure Data Management Solution including Azure Data Factory, Azure Databricks, Azure Blob storage (Gen2) and Azure Synapse

  • KNOWLEDGE & TECHNICAL SKILLS

  • Familiar with ETL/ELT framework, data warehousing concepts, data management framework and data lifecycle processes.

  • Experienced in handling and processing different types of data (structured, semi-structured and unstructured).

  • Strong knowledge in various database technologies (RDBMS, NoSQL and columnar).

  • Preferably with a good understanding of data analytics and data visualization, strongly prefer Power BI and Tableau.

  • Strong understanding of programming languages like Python, Scala, Java, R, Shell and PLSQL

  • Good understanding on Master Data Management (MDM) and Data Governance Tools preferring Informatica technologies

  • Experienced working in insurance industry will be an added advantage.

  • Ability to communicate and present technical information in a clear and unambiguous manner.

  • Strong ability to work independently and cooperate with diverse teams in a multiple stakeholder’s environment.

  • Strong sense of work ownership, high affinity with anything data and a desire for constant improvements.

  • Experience in API development and integration.

    E.g. SOAP, RestAPI

  • Build and modify APIs(Restful) and programs using Phyton and Java

  • Required Skill Profession

    Computer Occupations


    • Job Details

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    The Work Culture

    An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at FWD Life Insurance Corporation adheres to the cultural norms as outlined by Expertini.

    The fundamental ethical values are:

    1. Independence

    2. Loyalty

    3. Impartiapty

    4. Integrity

    5. Accountabipty

    6. Respect for human rights

    7. Obeying Malaysia laws and regulations

    What Is the Average Salary Range for Senior Data Engineer Positions?

    The average salary range for a varies, but the pay scale is rated "Standard" in Kampung Haji Abdullah Hukum. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.

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    Key qualifications for Senior Data Engineer typically include Computer Occupations and a list of qualifications and expertise as mentioned in the job specification. The generic skills are mostly outlined by the . Be sure to check the specific job listing for detailed requirements and qualifications.

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    Interview Tips for Senior Data Engineer Job Success

    FWD Life Insurance Corporation interview tips for Senior Data Engineer

    Here are some tips to help you prepare for and ace your Senior Data Engineer job interview:

    Before the Interview:

    Research: Learn about the FWD Life Insurance Corporation's mission, values, products, and the specific job requirements and get further information about

    Other Openings

    Practice: Prepare answers to common interview questions and rehearse using the STAR method (Situation, Task, Action, Result) to showcase your skills and experiences.

    Dress Professionally: Choose attire appropriate for the company culture.

    Prepare Questions: Show your interest by having thoughtful questions for the interviewer.

    Plan Your Commute: Allow ample time to arrive on time and avoid feeling rushed.

    During the Interview:

    Be Punctual: Arrive on time to demonstrate professionalism and respect.

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    Follow Up: Send a thank-you email to the interviewer within 24 hours.

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    Final Thought:

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