Manulife
Financial Services
DataEngineer
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Data Engineer at Manulife. Skills: Data engineering, Data architecture, Data pipelines, Cloud platforms. Design data infrastructure. Build data infrastructure”
Industry & Context.
Problem-solving; Troubleshoot data pipelines
What They're Looking For.
Must Have
Bachelor's or master's degree, 10+ years of experience, Advanced SQL expertise, ETL/ELT pipeline design, Azure data ecosystem experience, PySpark, Python, SQL proficiency, Big data frameworks experience, Data visualization tools knowledge, Data ingestion pipelines experience, Data modeling understanding, Data warehouse architecture understanding, Data lake architecture understanding, Cloud platforms experience, Containerization tools experience, Orchestration tools experience, Version control systems proficiency, Cloud security best practices understanding
Nice to Have
Analytical thinking, Problem-solving abilities, Ability to work independently, Manage complex requirements, Excellent communication skills, Passion for learning
What You'll Do.
Design data infrastructure
Build data infrastructure
Maintain data infrastructure
Develop data pipelines
Manage data pipelines
Implement data orchestration
Build ETL/ELT pipelines
Maintain ETL/ELT pipelines
Contribute to data platform modernization
Enhance reporting platforms
Support reporting platforms
Partner with business stakeholders
Understand data needs
Understand analytical requirements
Translate business problems
Communicate analytical findings
Support advanced analytics
Develop reusable frameworks
Develop automation scripts
Develop analytical tools
Build containerized data solutions
Build analytics platforms
Evaluate emerging technologies
Recommend innovative solutions
Monitor data pipelines
Optimize data pipelines
Troubleshoot data pipelines
Ensure data integrity
Ensure data governance
Document data sources
Validate data sources
Support development lifecycle
Contribute to planning
Collaborate across teams
Drive continuous improvement
Contribute to team success
How You'll Work.
Team & Collaboration
Cross-functional teams; Team members; Stakeholders
Communication Scope
Communicate findings; Technical audiences; Business audiences
Process & Methodology
Roadmap planning
Full Job Description
Join our Group Benefits Product Data Analytics team—a diverse and high-performing group dedicated to delivering accurate data, insightful visualizations, and advanced analytics that drive business decisions and improve customer outcomes. We are seeking a Data Engineer to play a key role in designing and building scalable data solutions that power business intelligence and analytics initiatives. This position spans the full data lifecycle, including data sourcing, transformation, storage, quality, and lineage, while enabling modern data platforms and capabilities. **Position Responsibilities:** **Data Engineering & Architecture** * Design, build, and maintain scalable and efficient data infrastructure for data ingestion, transformation, storage, and analysis * Develop and manage end-to-end data pipelines with a focus on data quality, reliability, and lineage * Implement data orchestration processes, including sourcing, cleansing, enrichment, and validation * Build and maintain robust ETL/ELT pipelines with strong fault tolerance and continuous integration **Data Platform & Solutions Development** * Design and develop data models, pipelines, and applications to enable efficient data workflows * Integrate data from enterprise systems, data lakes, and other internal/external sources * Contribute to data platform modernization initiatives and roadmap planning * Enhance and support enterprise data and reporting platforms **Business & Analytics Collaboration** * Partner with business stakeholders to understand data needs, KPIs, and analytical requirements * Translate business problems into data and analytics solutions, including prototypes and mock-ups * Deliver insights and communicate analytical findings to non-technical audiences * Support advanced analytics use cases, including descriptive and prescriptive analytics **Advanced Data & Innovation** * Develop reusable frameworks, automation scripts, and analytical tools * Build containerized data solutions and analytics p
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