Client is seeking an experienced Data Architect who can work with a team of domain and solution architects to design and support our data lake and ecosystem. The position will be part of the Data and AI architecture team. The candidate must have a strong analytics mindset, a passion for innovation, and the ability to build and maintain strong partnerships at all levels across our enterprise. We are looking for individuals that thrive within an Agile team-based framework. With our focus on Data management and building out our future Data platform, we are proactively seeking top talent to join our team to help us create and implement our new data lake and analytics platform.
- Lead / support data architecture discussion and design, participating in the design of the integration and Data Lakes architecture and analytics solutions
- Assist other data architects to develop and maintain enterprise integration and Data Lake architecture standards and guiding principles
- Support the assessment and optimization of the current architecture for scalability and performance
- Lead / support efforts in the standardization of data definition, development of data models, and data quality and ownership practices
- Own the the conceptual and logical design of the enterprise data model(s) and guide the implementation of the physical data model
- Ensure that solution design and implementation align to target state architecture standards and principles, and identify when it is necessary to modify the architecture to accommodate solution needs
- Collaborate with scrum masters and business leaders for all projects involving enterprise data
- Along with other data architects, develop and maintain current state architecture models and artifacts
- Work to address data-related problems relating to system integration, compatibility, and multiple-platform integration
- Identify and develop opportunities for data reuse, migration, or retirement
- Participate in data strategy and roadmap exercises
- Participate in Enterprise security and other enterprise architecture initiatives
- Provide excellent service, leadership, communication, problem solving and decision making skills.
- Demonstrate strong prioritization, time management and organizational skills.
Required Skills and Experience:
- Current and emerging techniques for obtaining data from a variety of sources; knowledge of data architecture and data modeling
- Big Data ecosystems
- Data analytics including ML/AI and data pipelines
- Data Lakes and Data-centric systems, data architecture, data modelling, and database design.
- Large scale data management in a complex multi-source, multi-product/ team environment. Exposure to Data Lake governance would be a plus
- Break down complex projects and problems into actionable tasks that be delivered quickly and iteratively and provide value to the business stakeholders
- Coordinate with the SSIS department to identify future needs and requirements, supporting all translation user requirements and business use cases to conceptual, logical, and physical data models and workflow processes.
- Translate a business glossary into logical and physical data models, and coach/ support data modelers, solution developers and SSIS in their development/ testing/ implementation effort.
- Work with a wide variety of data ranging between structured and unstructured datasets
- Own the KPIs to measure the performance of the data ecosystem and provide visibility to senior leadership team
- Working experience with cloud-based data warehouse technologies such as Google Cloud Platform, AWS, Microsoft Azure is highly desired.
- Strong experience working in an Agile (SCRUM, Kanban etc.) development environment is highly desirable
Additional Skills "Nice to Have":
Previous experience with/integrating with the following considered beneficial:
- Previous experience in other financial industry technology areas such as Treasury systems, self-service banking channels, etc.
- Familiarity with current and evolving strategies in the management and analysis of financial regulatory data e.g. FINRA
- Familiarity with regulations pertaining to data handling in the payments space e.g. Payment Card Industry Data Security Standards (PCI DSS), PIPEDA and Privacy Act
- Public or private cloud environments
- Experience in designing / building solutions using Google Cloud Platforms (GCP) stack including technologies such as BigQuery, DataFlow, * Cloud Function, Data Fusion, Big Table, Firestore, Cloudbuild, Cloud Composer, etc.