Hong Kong
Live, first seen by us 78 days agoWorking Arrangement HybridRead the full posting
Employment type in the employer’s posting: Full timeFrom the employer’s posting
Mentor and coach data engineers and guide their technical work
Design, develop and manage data pipelines for extracting, transforming and loading data
Continuously optimize ETL processes for speed, latency and batch or real-time needs
Design data quality checks, validation rules and testing plans
Lead end-to-end data architecture with business leads and data architects
Mentor and coach data engineers on the team, providing technical guidance and leadership
Design, develop, and manage data pipelines that facilitate the detailed extraction, transformation, and loading of data from diverse sources
Continuously improve and optimize ETL processes to enhance data flow efficiency, minimize latency
Design testing plans, develop and implement data quality checks, validation rules
design, implement, and lead end-to-end architecture based on business requirements
Bachelor’s degree in computer science, Information Technology, or a related field. Master's degree is a plus.
10+ years of experience as a Data Engineer, with a track record of efficiently implementing and maintaining data pipelines, scheduling, monitoring, notification, and ETL processes using Azure Data Factory, Databricks, Python\Pyspark, Java, Scala.
Understanding of Azure infrastructure; subscriptions, resource groups, resources, access control with RBAC (role-based access control), integrations with Azure AD and Azure security principles INTERNAL (user group, service principal, managed identity), network concepts (VNet, Subnet, NSG rules, private endpoints), password\credential\key management and data protection.
Experience deploying and integrating Azure Data Services (ADF, Databricks) using DevOps tools and principles: GitHub Repository, Jenkins CI\CD pipelines, integrated unit tests, etc.
Knowledge of Azure Data Lake Storage (ADLS Gen2) and its topology on blob storage with file hierarchy, storage account, containers, and folders.
Proficient in data mart fact and dimension design concepts, ETL\ELT logic to perform upsert and type-2, and applying\implementing with Python\PySpark\store proc\SQL in ADLS (with Lakehouse architecture using Databricks) or in Azure Synapse (with Dedicated SQL pool).
Experience with LLM and AI tools.
Experience using Unity Catalog.
Experience using Power BI to connect to sources with ADLS (including Delta Lake), Databricks SQL, Azure Synapse (SQL pool), design semantic layer\data models, create\publish reporting content (data sets\paginate report\interactive dashboard), and manage workspaces.
Required Qualifications: • Bachelor’s degree in computer science, Information Technology, or a related field. Master's degree is a plus. • 10+ years of experience as a Data Engineer, with a track record of efficiently implementing and maintaining data pipelines, scheduling, monitoring, notification, and ETL processes using Azure Data Factory, Databricks, Python\Pyspark, Java, Scala.
We strive to attract, develop and retain a workforce that is as diverse as the customers we serve and to foster an inclusive work environment that embraces the strength of cultures and individuals.
In the employer’s words · Read in context
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Day 78
Up longer than most. Similar jobs usually come down between day 6 and day 56.
Well past Manulife Financial’s usual: its jobs come down by about day 27.
From 13,649 similar postings that came down, and 179 of Manulife Financial’s. Coming down is not always a hire.
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Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
• Bachelor’s degree in computer science, Information Technology, or a related field. Master's degree is a plus. • 10+ years of experience as a Data Engineer, with a track record of efficiently implementing and maintaining data pipelines, scheduling, monitoring, notification, and ETL processes using Azure Data Factory, Databricks, Python\Pyspark, Java, Scala. • Understanding of Azure infrastructure; subscriptions, resource groups, resources, access control with RBAC (role-based access control), integrations with Azure AD and Azure security principles INTERNAL (user group, service principal, managed identity), network concepts (VNet, Subnet, NSG rules, private endpoints), password\credential\key management and data protection.
• Knowledge of Azure Data Lake Storage (ADLS Gen2) and its topology on blob storage with file hierarchy, storage account, containers, and folders. • Proficient in data mart fact and dimension design concepts, ETL\ELT logic to perform upsert and type-2, and applying\implementing with Python\PySpark\store proc\SQL in ADLS (with Lakehouse architecture using Databricks) or in Azure Synapse (with Dedicated SQL pool). Preferred Qualifications:
• Experience using Unity Catalog. • Experience using Power BI to connect to sources with ADLS (including Delta Lake), Databricks SQL, Azure Synapse (SQL pool), design semantic layer\data models, create\publish reporting content (data sets\paginate report\interactive dashboard), and manage workspaces. • Solid understanding of data privacy and compliance regulations and standard methodologies.
• 10+ years of experience as a Data Engineer, with a track record of efficiently implementing and maintaining data pipelines, scheduling, monitoring, notification, and ETL processes using Azure Data Factory, Databricks, Python\Pyspark, Java, Scala. • Understanding of Azure infrastructure; subscriptions, resource groups, resources, access control with RBAC (role-based access control), integrations with Azure AD and Azure security principles INTERNAL (user group, service principal, managed identity), network concepts (VNet, Subnet, NSG rules, private endpoints), password\credential\key management and data protection. • Experience deploying and integrating Azure Data Services (ADF, Databricks) using DevOps tools and principles: GitHub Repository, Jenkins CI\CD pipelines, integrated unit tests, etc.
• Understanding of Azure infrastructure; subscriptions, resource groups, resources, access control with RBAC (role-based access control), integrations with Azure AD and Azure security principles INTERNAL (user group, service principal, managed identity), network concepts (VNet, Subnet, NSG rules, private endpoints), password\credential\key management and data protection. • Experience deploying and integrating Azure Data Services (ADF, Databricks) using DevOps tools and principles: GitHub Repository, Jenkins CI\CD pipelines, integrated unit tests, etc. • Knowledge of Azure Data Lake Storage (ADLS Gen2) and its topology on blob storage with file hierarchy, storage account, containers, and folders.
• Experience deploying and integrating Azure Data Services (ADF, Databricks) using DevOps tools and principles: GitHub Repository, Jenkins CI\CD pipelines, integrated unit tests, etc. • Knowledge of Azure Data Lake Storage (ADLS Gen2) and its topology on blob storage with file hierarchy, storage account, containers, and folders. • Proficient in data mart fact and dimension design concepts, ETL\ELT logic to perform upsert and type-2, and applying\implementing with Python\PySpark\store proc\SQL in ADLS (with Lakehouse architecture using Databricks) or in Azure Synapse (with Dedicated SQL pool).
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New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Manulife is embarking on replacing and building new data capabilities to help fuel our bold ambition to become a digital customer leader! We are seeking a skilled and motivated Lead Data Engineer to join our diverse team and play a key role in implementing, optimizing, and maintaining assets that deliver these capabilities! The ideal candidate possesses a solid background in data engineering, ETL processes, and data integration, with a passion for understanding data to drive strategic business decisions.
Asia Group Functions Lead Data Engineer
Position Responsibilities:
• Leadership: Mentor and coach data engineers on the team, providing technical guidance and leadership to build a high-performing data engineering team. Use excellent leadership and communication skills to foster a collaborative and high-performing team culture. Ensure that team members are meeting project timelines and delivering high-quality solutions that meet the needs of the business.
• Domain Knowledge: Stay up-to-date with the latest tools and technologies and identify opportunities to enhance Manulife's data infrastructure. • Teamwork: Partner with other lead data engineers, data analysts, business collaborators, and data scientists to understand data requirements and translate them into effective data engineering solutions.
• Data Pipeline Development: Design, develop, and manage data pipelines that facilitate the detailed extraction, transformation, and loading of data from diverse sources. Leverage expertise in big data and cloud computing to ensure solutions are scalable, efficient, and effective.
• Data Mapping & Integration: Collaborate closely with multi-functional teams to understand and design schemas for data from various source systems and other transactional or application databases, ensuring accuracy and reliability.
• ETL Optimization: Continuously improve and optimize ETL processes to enhance data flow efficiency, minimize latency, and support real-time and batch processing requirements.
• Data Transformation: Implement data cleansing, enrichment, and transformation processes to ensure high-quality data is available for analysis and reporting.
• Data Quality Assurance: Design testing plans, develop and implement data quality checks, validation rules, and supervising mechanisms to maintain data accuracy and integrity.
•Platform Improvement: Collaborate with various technical resources from across the organization to identify and implement improvements to the infrastructure, integrations, and functionalities.
• Data Architecture: Work closely with business leads and data architects to design, implement, and lead end-to-end architecture based on business requirements.
• User Documentation: Develop and maintain detailed documentation for data pipelines, processes, and configurations to support seamless onboarding.
• Performance Monitoring: Monitor data pipeline performance and solve issues to ensure efficient data flow and proactively find opportunities for improvement.
• Data Governance and Compliance: Ensure consistency with data privacy and compliance standards throughout the data lifecycle.
Required Qualifications:
• Bachelor’s degree in computer science, Information Technology, or a related field. Master's degree is a plus.
• 10+ years of experience as a Data Engineer, with a track record of efficiently implementing and maintaining data pipelines, scheduling, monitoring, notification, and ETL processes using Azure Data Factory, Databricks, Python\Pyspark, Java, Scala.
• Understanding of Azure infrastructure; subscriptions, resource groups, resources, access control with RBAC (role-based access control), integrations with Azure AD and Azure security principles INTERNAL (user group, service principal, managed identity), network concepts (VNet, Subnet, NSG rules, private endpoints), password\credential\key management and data protection.
• Experience deploying and integrating Azure Data Services (ADF, Databricks) using DevOps tools and principles: GitHub Repository, Jenkins CI\CD pipelines, integrated unit tests, etc.
• Knowledge of Azure Data Lake Storage (ADLS Gen2) and its topology on blob storage with file hierarchy, storage account, containers, and folders.
• Proficient in data mart fact and dimension design concepts, ETL\ELT logic to perform upsert and type-2, and applying\implementing with Python\PySpark\store proc\SQL in ADLS (with Lakehouse architecture using Databricks) or in Azure Synapse (with Dedicated SQL pool).
Preferred Qualifications:
• Experience with LLM and AI tools.
• Experience using Unity Catalog.
• Experience using Power BI to connect to sources with ADLS (including Delta Lake), Databricks SQL, Azure Synapse (SQL pool), design semantic layer\data models, create\publish reporting content (data sets\paginate report\interactive dashboard), and manage workspaces.
• Solid understanding of data privacy and compliance regulations and standard methodologies.
• Excellent problem-solving skills and the ability to solve technical issues efficiently.
• Effective communication skills to collaborate with technical and non-technical partners.
• Thorough approach with a commitment to delivering high-quality work in a fast-paced environment.
When you join our team:
We’ll empower you to learn and grow the career you want.
We’ll recognize and support you in a flexible environment where well-being and inclusion are more than just words.
As part of our global team, we’ll support you in shaping the future you want to see.
About Manulife and John Hancock
Manulife Financial Corporation is a leading international financial services provider, helping people make their decisions easier and lives better. To learn more about us, visit https://www.manulife.com/en/about/our-story.html.
Manulife is an Equal Opportunity Employer
At Manulife/John Hancock, we embrace our diversity. We strive to attract, develop and retain a workforce that is as diverse as the customers we serve and to foster an inclusive work environment that embraces the strength of cultures and individuals. We are committed to fair recruitment, retention, advancement and compensation, and we administer all of our practices and programs without discrimination on the basis of race, ancestry, place of origin, colour, ethnic origin, citizenship, religion or religious beliefs, creed, sex (including pregnancy and pregnancy-related conditions), sexual orientation, genetic characteristics, veteran status, gender identity, gender expression, age, marital status, family status, disability, or any other ground protected by applicable law.
It is our priority to remove barriers to provide equal access to employment. A Human Resources representative will work with applicants who request a reasonable accommodation during the application process. All information shared during the accommodation request process will be stored and used in a manner that is consistent with applicable laws and Manulife/John Hancock policies. To request a reasonable accommodation in the application process, contact hr@manulife.com.
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Working Arrangement Hybrid
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