1 018 Team Data jobs in Hong Kong

Responsibilities :

• Handle, integrate and govern external data procurement requests
• Lead and support external data management activities in the external data acquisition process.
• Support vendors management (service quality and performance monitoring)
• Document external data sources, usage and other information to support management reporting
• Support other data management tasks as assigned

Requirements :

• Degree or above in finance, computer science, IT management, statistics, business administration, project management or relevant disciplines
• Minimum 3 years' working experience, preferably in data management particularly in external data
• Experience in external data procurement would be desirable
• Excellent communication skill and with team-work spirit
• Have can-do attitude and attentive to details
• Familiar with Microsoft Office (including Chinese typing)

Candidates with less experience will be considered as Associate Data Analyst

Join to apply for the Data Scientist (Marketing Data Science) role at Klook .

Get AI-powered advice on this job and more exclusive features.

We are Asia’s leading platform for experiences and travel services, and we believe that we can help bring the world closer together through experiences. Founded in 2014 by three travelers, Klook inspires and enables moments of joy for travelers with over half a million curated experiences across 2,700 destinations. Our international community includes over 1,800 employees in 30+ locations, guided daily by our 6 core values: Customer First, Push Boundaries, Critical Thinking, Build for Scale, Less is More, Win as One.

We never settle and strive to achieve greater heights in the dynamic travel era. If you share our belief in the wonders of travel, consider joining us.

• Develop and implement advanced marketing measurement models, including Media Mix Modeling (MMM) and Multi-Touch Attribution (MTA), to evaluate and improve ROI across channels (search, social, display, etc.).
• Analyze campaign performance using data from Google Analytics, Meta Ads (Facebook/Instagram), and other sources to provide insights on channel effectiveness and customer behavior.
• Apply view-through attribution modeling for display and social campaigns to credit conversions from ad views (not just clicks).
• Design and execute experiments (e.g., A/B tests) to measure campaign lift and optimize marketing spend.
• Collaborate with cross-functional teams (Marketing, Data, Product) to translate findings into strategic recommendations and actionable plans.
• Communicate insights and reports to stakeholders to guide data-driven decision-making for marketing and budgeting.

• Education & Experience: Bachelor’s degree or higher in Statistics, Data Science, Marketing, or related field. Minimum 5 years of relevant experience in marketing analytics or data science.
• Technical Skills: Proficiency in Python, R, and SQL for data analysis and model development. Hands-on experience with Google Analytics and Meta Ads platforms.
• Domain Expertise: Demonstrated expertise in MMM, MTA, or view-through contribution modeling to assess marketing performance. Familiarity with digital advertising metrics and attribution models.
• Analytical & Communication: Strong statistical analysis skills and the ability to derive clear insights from complex data. Excellent communication skills to present findings to both technical and non-technical stakeholders.
• Teamwork: Ability to work in an in-office, cross-functional team environment. Self-motivated with strong problem-solving skills and attention to detail.

Klook is proud to be an equal opportunity employer. We hire talented and passionate people of all backgrounds and are dedicated to creating a welcoming and supportive culture where everyone belongs.

Note: Klook does not accept unsolicited resumes from agencies. Any submission must follow our internal processes and agreements.

Get AI-powered advice on this job and more exclusive features.

Reporting to the Data & Analytics Director, this position is for a Data Engineer who is passionate about building robust, scalable data solutions and lightweight AI applications. While our ecosystem is built on the Google Cloud Platform (GCP), we value strong engineering fundamentals and welcome candidates with experience in similar technologies from other cloud environments (like AWS or Azure).

You will work closely with data analysts, media teams and business stakeholders to build the foundational technology that drives business growth and operational efficiency. A key focus of this role will be developing and deploying lightweight internal tools on Google Cloud Run that are powered by Generative AI. This role offers the opportunity to directly collaborate with clients and vendors, implementing data & analytics strategies for OMG’s clients. You will contribute to our mission of empowering our agencies with advanced data solutions.

• Data Pipeline Architecture & Development: Design, build, and maintain resilient and scalable ETL/ELT pipelines on GCP to process data and load it into BigQuery.
• Workflow Automation & Solution Design: Proactively identify opportunities to automate day-to-day workflows and repetitive tasks across the business. Design and implement automated solutions that reduce manual effort, increase efficiency, and allow teams to focus on higher-value activities.
• Develop Lightweight AI-Powered Tools: Build simple, internal-use web tools using Python frameworks (e.g., Streamlit, Flask). The role involves writing scripts and developing lightweight applications that integrate Generative AI models (e.g., Google's Gemini via Vertex AI) to support tasks like natural language querying, report summarization, and basic insight generation.
• Application Deployment: You will be responsible for containerizing these AI-powered applications with Docker and deploying them on Google Cloud Run, our primary service for hosting container-based applications and APIs.
• Data Governance & Quality: Implement and automate data quality checks to ensure the accuracy and consistency of data within our BigQuery data warehouse.
• Technical Strategy & Innovation: Lead the exploration and implementation of Generative AI use cases within our data platform. You will evaluate new models and services to build innovative solutions that create tangible business value.

• 3+ years of experience in a data engineering or similar software engineering role.
• Strong programming skills in Python, with experience using data-related libraries (e.g., Pandas, Polars).
• Proven experience with at least one major cloud platform (GCP, AWS, or Azure), with a willingness to specialize in the GCP ecosystem.
• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related technical field is a plus.

While direct experience with our specific tools is a plus, we value transferable skills and a strong foundation in equivalent technologies.

• Data Warehousing: Google BigQuery (Equivalent experience: Snowflake, Amazon Redshift, Azure Synapse)
• Data Processing & Orchestration: Cloud Composer (Airflow), Cloud Dataflow (Spark), and Cloud Functions (Equivalent experience: AWS Lambda, Azure Functions)
• Application & API Deployment: Google Cloud Run, using Docker for containerization. (Equivalent experience: Kubernetes, AWS Fargate, Azure Container Apps)
• Generative AI: Experience or strong interest in integrating large language models (LLMs) via APIs (e.g., Google Vertex AI, OpenAI).
• Web Application Development: Experience in building lightweight data applications or internal tools with Python frameworks (e.g., Streamlit, Flask).
• Domain Knowledge: Familiarity with digital marketing tools and ad platforms (e.g., Google Ads, Meta Ads, Google Analytics) is a plus.

• Analytical Mindset: You have strong analytical and problem-solving abilities to tackle complex data challenges.
• Excellent Communicator: You can effectively partner with both technical and non-technical stakeholders to translate business needs into technical solutions.
• Strong Sense of Project Ownership: You can take technical projects from conception to completion with autonomy and accountability.

• Full-time

• Engineering, Project Management, and Information Technology

• Advertising Services

• Work in the Customer Data InnoStation to assist business teams in data exploration.
• Understand available datasets on travel patterns, loyalty programs, app browsing history, and video analytics.
• Facilitate business teams in utilizing datasets for ETL, data visualization, and segmentation.
• Support supervisors and managers in conducting data analytics, preparing reports, and maintaining dashboards.
• Assist in operating and monitoring the Customer Data InnoStation, including activity logging and usage monitoring.
• Assist in the development of innovative data-driven services.

• Degree in Computer Science, Data Science, Information Technology, or related disciplines.
• Strong interpersonal and communication skills in both written and spoken English and Chinese.
• 3+ years of hands-on experience in data analytics is preferred.

• Experience with one or more of the following tools and technologies is an advantage:

• Data visualization tools (e.g., PowerBI)

• Database programming (e.g., SQL)
• Programming languages (e.g., Python, R)
• Frontend web technologies (e.g., HTML5, web scraping)
• Process automation (e.g., Power Automate)

Job Description

• Create and implement analytical models with meaningful insights, that yield significant insights to promote business growth and reduce risks.
• Explore various data sources and perform exploratory data analysis to identify relevant data for addressing specific challenges and business needs. Create valuable features that enhance analytics capabilities.
• Collaborate with stakeholders to propose and assess actions for performance improvement.
• Build business analytics capabilities aligned with identified use cases.
• Develop visualizations and dashboards to effectively communicate analytics results to stakeholders.
• Act as a persuasive storyteller, translating analytics findings into clear, understandable language for stakeholders.
• Stay up to date with the latest Microsoft Fabric/ Power BI features and functionalities.
• Offer technical and functional support to internal users for BI tools and reporting solutions.
• Collaborate with the data engineering and governance teams to adhere to schedules, fulfill requirements, and address any changes, issues, or risks that may arise.

Requirements

• Bachelor's degree in Business Analytics, Mathematics, Statistics, Computer Science, Information Engineering, or related disciplines.
• 5+ years of experience in a data analysis or business intelligence role, with a strong understanding of business operations and data requirements.
• Sound knowledge in statistics, with data analytics techniques like predictive, prescriptive and machine learning.
• Proficient in SQL, Python and/or R to extract, clean, and manipulate data from various sources for analysis and reporting.
• Experience in Azure Databricks and using AI for data analytics would be an advantages but not a must
• Develop, maintain, and manage advanced Power BI dashboards, visualizations, and reports to provide key business insights.
• Analyze large datasets to identify trends, patterns, and business insights that inform strategy and decision-making.
• Experience in data modeling and analysis techniques, with the ability to understand and construct critical business factors and characteristics.
• Proven ability to manage project development from inception to deployment, demonstrating leadership and collaboration in a team-oriented environment.
• Proven experience as a data analyst in delivering successful data products
• Ability to navigate in a complex environment to drive outcome with stakeholders
• Energetic, proactive adaptive problem solver, organized, flexible and comfortable navigating through ambiguity
• Proficient in English, excellent communication both verbal and written

Responsibilities :

• Lead and support data management activities in the areas of data security , data standards and data dictionary management etc.
• Work with data stewards in various business areas to drive data quality and customer data management
• Conduct research for regulatory requirements and best market practices of data governance
• Support other data management tasks as assigned

Requirements :

• Degree or above in computer science, IT management, statistics, business administration or relevant disciplines
• Minimum 3 years' working experience, preferably in data management field.
• Familiar with Microsoft Office (including Chinese typing), SQL / Python preferred.
• Candidates with less experience will be considered as Associate Data Analyst.

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 to the business, and we support our people's career ambitions. We pledge to make Prudential a place where you can Connect, Grow, and Succeed.

Job Responsibilities

• Design, build, and maintain scalable and efficient ETL/ELT pipelines in Azure Databricks to process structured, semi-structured, and unstructured insurance data from multiple internal and external sources.
• Collaborate with data architects, modellers, analysts, and business stakeholders to gather data requirements and deliver fit-for-purpose data assets that support analytics, regulatory, and operational needs.
• Develop, test, and optimize data transformation routines, batch and streaming solutions (leveraging tools such as Azure Data Factory, Data Lake Storage Gen2, Azure Event Hubs, and Kafka) to ensure timely and accurate data delivery.
• Implement rigorous data quality, validation, and cleansing procedures—with a focus on enhancing reliability for high-stakes insurance use cases, reporting, and regulatory outputs.
• Integrate Informatica tools to facilitate data governance, including the capture of data lineage, metadata, and data cataloguing as required by regulatory and business frameworks.
• Ensure robust data security by following best practices for RBAC, managed identities, encryption, and compliance with Hong Kong's PDPO, GDPR, and other relevant regulatory requirements.
• Automate and maintain deployment pipelines using GitHub Actions to ensure efficient, repeatable, and auditable data workflows and code releases.
• Conduct root cause analysis, troubleshoot pipeline failures, and proactively identify and resolve data quality or performance issues.
• Produce and maintain comprehensive technical documentation for pipelines, transformation rules, and operational procedures to ensure transparency, reuse, and compliance.
• Apply subject matter expertise in Hong Kong Life and General Insurance to ensure that development captures local business needs and industry-specific standards.

Job Requirements

• Bachelor's degree in Information Technology, Computer Science, Data Engineering, or a related discipline.
• 6+ years of experience as a data engineer, building and maintaining ETL/ELT processes and data pipelines on Azure Databricks (using PySpark or Scala), with a focus on structured, semi-structured, and unstructured insurance data.
• Strong experience orchestrating data ingestion, transformation, and loading workflows using Azure Data Factory and Azure Data Lake Storage Gentwo.
• Advanced proficiency in Python and Spark for data engineering, data cleaning, transformation, and feature engineering in Databricks for analytics and machine learning.
• Experience integrating batch and streaming data sources via Kafka or Azure Event Hubs for real-time or near-real-time insurance applications.
• Hands-on use of Informatica for data quality, lineage, and governance to support business and regulatory standards in insurance.
• Familiarity with automation and CI/CD of Databricks workflows using GitHub Actions.
• Understanding of data security, RBAC, Key Vault, encryption, and best practices for compliance in the insurance sector.
• Experience optimizing data pipelines to support ML workflows and BI/reporting tools.
• Excellent command of English and Chinese – both written and spoken.

Prudential is an equal opportunity employer.
We provide equality of opportunity of benefits for all who apply and who perform work for our organisation 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.

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 to the business, and we support our people's career ambitions. We pledge to make Prudential a place where you can Connect, Grow, and Succeed.

Job Responsibilities

• Design, build, and maintain scalable and efficient ETL/ELT pipelines in Azure Databricks to process structured, semi-structured, and unstructured insurance data from multiple internal and external sources.
• Collaborate with data architects, modellers, analysts, and business stakeholders to gather data requirements and deliver fit-for-purpose data assets that support analytics, regulatory, and operational needs.
• Develop, test, and optimize data transformation routines, batch and streaming solutions (leveraging tools such as Azure Data Factory, Data Lake Storage Gen2, Azure Event Hubs, and Kafka) to ensure timely and accurate data delivery.
• Implement rigorous data quality, validation, and cleansing procedures—with a focus on enhancing reliability for high-stakes insurance use cases, reporting, and regulatory outputs.
• Integrate Informatica tools to facilitate data governance, including the capture of data lineage, metadata, and data cataloguing as required by regulatory and business frameworks.
• Ensure robust data security by following best practices for RBAC, managed identities, encryption, and compliance with Hong Kong's PDPO, GDPR, and other relevant regulatory requirements.
• Automate and maintain deployment pipelines using GitHub Actions to ensure efficient, repeatable, and auditable data workflows and code releases.
• Conduct root cause analysis, troubleshoot pipeline failures, and proactively identify and resolve data quality or performance issues.
• Produce and maintain comprehensive technical documentation for pipelines, transformation rules, and operational procedures to ensure transparency, reuse, and compliance.
• Apply subject matter expertise in Hong Kong Life and General Insurance to ensure that development captures local business needs and industry-specific standards.

Job Requirements

• Bachelor's degree in Information Technology, Computer Science, Data Engineering, or a related discipline.
• 6+ years of experience as a data engineer, building and maintaining ETL/ELT processes and data pipelines on Azure Databricks (using PySpark or Scala), with a focus on structured, semi-structured, and unstructured insurance data.
• Strong experience orchestrating data ingestion, transformation, and loading workflows using Azure Data Factory and Azure Data Lake Storage Gen2.
• Advanced proficiency in Python and Spark for data engineering, data cleaning, transformation, and feature engineering in Databricks for analytics and machine learning.
• Experience integrating batch and streaming data sources via Kafka or Azure Event Hubs for real-time or near-real-time insurance applications.
• Hands-on use of Informatica for data quality, lineage, and governance to support business and regulatory standards in insurance.
• Familiarity with automation and CI/CD of Databricks workflows using GitHub Actions.
• Understanding of data security, RBAC, Key Vault, encryption, and best practices for compliance in the insurance sector.
• Experience optimizing data pipelines to support ML workflows and BI/reporting tools.
• Excellent command of English and Chinese – both written and spoken.

Prudential is an equal opportunity employer. We provide equality of opportunity of benefits for all who apply and who perform work for our organisation 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.

Get AI-powered advice on this job and more exclusive features.

Reporting to the Data & Analytics Director, this position is for a Data Engineer who is passionate about building robust, scalable data solutions and lightweight AI applications. While our ecosystem is built on the Google Cloud Platform (GCP), we value strong engineering fundamentals and welcome candidates with experience in similar technologies from other cloud environments (like AWS or Azure).

You will work closely with data analysts, media teams and business stakeholders to build the foundational technology that drives business growth and operational efficiency. A key focus of this role will be developing and deploying lightweight internal tools on Google Cloud Run that are powered by Generative AI. This role offers the opportunity to directly collaborate with clients and vendors, implementing data & analytics strategies for OMG’s clients. You will contribute to our mission of empowering our agencies with advanced data solutions.

• Data Pipeline Architecture & Development: Design, build, and maintain resilient and scalable ETL/ELT pipelines on GCP to process data and load it into BigQuery.
• Workflow Automation & Solution Design: Proactively identify opportunities to automate day-to-day workflows and repetitive tasks across the business. Design and implement automated solutions that reduce manual effort, increase efficiency, and allow teams to focus on higher-value activities.
• Develop Lightweight AI-Powered Tools: Build simple, internal-use web tools using Python frameworks (e.g., Streamlit, Flask). The role involves writing scripts and developing lightweight applications that integrate Generative AI models (e.g., Google's Gemini via Vertex AI) to support tasks like natural language querying, report summarization, and basic insight generation.
• Application Deployment: You will be responsible for containerizing these AI-powered applications with Docker and deploying them on Google Cloud Run, our primary service for hosting container-based applications and APIs.
• Data Governance & Quality: Implement and automate data quality checks to ensure the accuracy and consistency of data within our BigQuery data warehouse.
• Technical Strategy & Innovation: Lead the exploration and implementation of Generative AI use cases within our data platform. You will evaluate new models and services to build innovative solutions that create tangible business value.

• 3+ years of experience in a data engineering or similar software engineering role.
• Strong programming skills in Python, with experience using data-related libraries (e.g., Pandas, Polars).
• Proven experience with at least one major cloud platform (GCP, AWS, or Azure), with a willingness to specialize in the GCP ecosystem.
• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related technical field is a plus.

While direct experience with our specific tools is a plus, we value transferable skills and a strong foundation in equivalent technologies.

• Data Warehousing: Google BigQuery (Equivalent experience: Snowflake, Amazon Redshift, Azure Synapse)
• Data Processing & Orchestration: Cloud Composer (Airflow), Cloud Dataflow (Spark), and Cloud Functions (Equivalent experience: AWS Lambda, Azure Functions)
• Application & API Deployment: Google Cloud Run, using Docker for containerization. (Equivalent experience: Kubernetes, AWS Fargate, Azure Container Apps)
• Generative AI: Experience or strong interest in integrating large language models (LLMs) via APIs (e.g., Google Vertex AI, OpenAI).
• Web Application Development: Experience in building lightweight data applications or internal tools with Python frameworks (e.g., Streamlit, Flask).
• Domain Knowledge: Familiarity with digital marketing tools and ad platforms (e.g., Google Ads, Meta Ads, Google Analytics) is a plus.

• Analytical Mindset: You have strong analytical and problem-solving abilities to tackle complex data challenges.
• Excellent Communicator: You can effectively partner with both technical and non-technical stakeholders to translate business needs into technical solutions.
• Strong Sense of Project Ownership: You can take technical projects from conception to completion with autonomy and accountability.

• Full-time

• Engineering, Project Management, and Information Technology

• Advertising Services