Senior Data Architect shaping data architecture strategy within the U.S. Segment at Manulife. Leading implementation of data integration strategies and optimizing data solutions.
Responsibilities
Leads the development and implementation of data integration and migration strategies for large datasets.
Designs and architects highly scalable data pipelines to load data from various source systems.
Designs, architects, and maintains data models, data warehouses, and data lakes optimized for scalability and performance.
Designs data architecture and IT solutions to ensure data is stored properly, usable by business units, and protected from attacks.
Optimizes data solutions for performance and scalability, utilizing techniques such as data partitioning, distributed processing, and data compression.
Identifies the needs of the data lakes and data warehouses, the data that is available, and creates a blueprint for creating, testing and maintaining them.
Works with database administrators and data analysts to ensure they can easily use and access data.
Works with management to create databases that will be usable and store the required information.
Addresses issues with data migration (e.g., validation, clean-up and mapping) and understands the importance of Data Dictionaries.
Documents data architectures, technical processes, and performance optimization strategies.
Documents data interfaces and movement which includes frequency of movement, data transformations, and any aggregation or calculations.
Integrates views of data by working with business team members and application designers to determine data requirements (e.g., availability, volumes).
Defines data architecture standards and guidelines, and how to use the architected databases.
Helps ensure a focus on data quality, working closely with business team members to determine its importance.
Software/platform/infrastructure architecture plans to support business strategy and outcomes.
Defines the overall integration of Data and ML pipelines across the data supply chain and defines the technical and operational design of these pipelines.
Implements mechanisms to monitor and prevent unethical use of data, such as bias in algorithms or discriminatory practices.
Requirements
Experience architecting, designing and developing large-scale data solutions and enterprise-wide systems
Strong knowledge of data management skills (e.g., Hadoop, NoSQL, Spark), metadata management, big data management
Expert knowledge of structured analysis and design techniques
Knowledge across data technology stack (e.g., Azure Data Factory, Databricks, Spark, Python, Synapse)
Strong understanding of data management, from RDBMS to NoSQL data models
Knowledge of ETL and data integration tools and technologies
Software development experience using multiple languages (e.g., Python , Java, C, C++, C#)
Understanding of logical designs of how databases will link to each other and the flow of data between stages
Ability to use AI to support data management strategies.
Provides professional advice – takes a lead role of process or program execution
Is accountable for own work and contributes to setting standards through expertise in own job discipline that impact others’ deliverables
Work is guided by cascaded policies or business plans
May lead medium to large size projects or work streams with moderate resource requirements, risk and/or complexity with multiple teams representing different interests
Benefits
health, dental, mental health, vision, short- and long-term disability, life and AD&D insurance coverage
adoption/surrogacy and wellness benefits
employee/family assistance plans
various retirement savings plans (including pension and a global share ownership plan with employer matching contributions)
financial education and counseling resources
generous paid time off program including holidays, vacation, personal, and sick days
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