Senior Data Engineer, Retirement Operations

Job Requirements:

• 4 or more years of experience as a data engineer or data scientist with proficiency in big data engineering
• Ability to collaborate effectively in a large highly matrixed organization with many different data teams
• Expert in SQL and PySpark
• Knowledge of database systems, data lakes, and NoSQL databases
• Knowledge of data warehouse concepts and architectures and working with Parquet files
• Proficiency in using job orchestration tools like Roadrunner
• Familiarity with data quality and data modelling tools
• Proficiency in using version control systems like Git for managing codebase
• Experience with Azure cloud environment especially Azure Data Factory, ADLS, and Databricks
• Experience with integrating to back-end/legacy environments

Preferred Qualifications:

• Experience working on Agile teams using Scrum and Kanban
• Experience with Call Centre analytics and operations
• Experience with vector databases and AI engineering
• Bilingualism (English and French) is an asset. If the successful candidate is in Québec, proficiency in both languages will be required to support clients from various provinces outside of Quebec.
• Familiarity with Tabular Editor & Roadrunner
• Knowledge of Manulife & John Hancock Retirement products systems and operations.
• Decision Authority:
• Leads projects or work streams independently and contributes to their planning
• Act as professional expertise information resource in creating data engineering solutions to business problems
• Requires advanced problem-solving skills
• 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. This job description is not a comprehensive listing of all job duties required for this role. We reserve the right to change these duties or assign additional duties at any time with or without notice.
• The role being advertised is an existing vacancy.
• 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.
• This job description is not a comprehensive listing of all job duties required for this role. We reserve the right to change these duties or assign additional duties at any time with or without notice.

About Manulife and John Hancock

Responsibilities

• Collaborate with fellow data engineering colleagues across the organization to deliver secure, reliable, and efficient data engineering solutions
• Designs, builds, and maintains reliable, efficient and scalable data infrastructure for data collection, storage, transformation, and analysis.
• Implements data orchestration pipelines, data sourcing, cleansing, augmentation, and quality control processes.
• Collaborates with business and technology stakeholders to understand current and future data infrastructure requirements.
• Designs, builds and maintains scalable data solutions including data pipelines, data models, and applications for efficient and reliable data workflow; including those specifically tailored for machine learning workflows.
• Designs, implements, and maintains existing and future data platforms like data warehouses, data lakes, data lakehouses for structured and unstructured data.
• Collaborates with Data Scientists and Engineers to create features and pre-process data for ML models and move data analysis models into production.
• Designs and develops analytical tools, algorithms, data landscape modernization roadmaps, and programs to support Data Engineering activities like writing scripts and automating tasks.
• Utilizes a variety of data interchange formats to ensure data requirements are met and continuously monitors data integrity across the organization.
• Deploys machine learning models with existing production systems and workflows, considering compatibility with other systems, data sources, and APIs.
• Designs and promotes effective use of data querying APIs to provide easy access to organizational data sources.
• Evaluates, integrates, and manages tools and frameworks within the data engineering ecosystem, ensuring compatibility and efficiency in model development and deployment.
• Designs and promotes data versioning and lineage tracking, including transparency and traceability for data used in ML model training and inference.