Description:
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 data engineer to join our dynamic 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.
Responsibilities
- Data Pipeline Development: Design, develop, and manage end-to-end data pipelines that facilitate the detailed extraction, transformation, and loading of data from diverse sources.
- 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 Enhancement: Collaborate with various technical resources from across the organization to identify and implement enhancements to the infrastructure, integrations, and functionalities.
- Data Architecture: Work closely with business leads and data architects to design, implement, and manage end-to-end architecture based on business requirements.
- User Documentation: Create and maintain comprehensive documentation for data pipelines, processes, and configurations to facilitate knowledge sharing and onboarding.
- Collaboration: Partner with other data engineers, data analysts, business collaborators, and data scientists to understand data requirements and translate them into effective data engineering solutions.
- Performance Monitoring: Monitor data pipeline performance and solve issues to ensure optimal data flow and proactively find opportunities for enhancement.
- Data Governance and Compliance: Ensure consistency with data privacy and compliance standards throughout the data lifecycle.