Requisition ID: 219399
Join a purpose driven winning team, committed to results, in an inclusive and high-performing culture.
As the Senior Manager, Risk Data & Governance, you will lead the governance, design, development and management of key data products including data models, optimal architecture and deployment solutions. This role is critical to the success of our data strategy, ensuring that valuable and reliable data assets are readily available to empower our business units and drive innovation. You will collaborate with data users in Global Risk Management (GRM), Data Governance, and Technology teams to define, prioritize, and deliver impactful data products in compliance with internal policies and industry regulations.
Is this role right for you? In this role, you will:
Data Modernization & Governance Advocacy
Act as a key advocate for data architecture best practices, considering data mesh and cloud-based options within the organization, promoting transparency, simplification, self-serve, and domain ownership principles
Support rapid prototyping and development of ETLs and data pipelines using Python, DBT, Airflow, Composer, SQL, and BigQuery.
Collaborate with data stewards and data owners to ensure data quality, lineage documentation and adherence to policies and regulatory requirements (e.g., OSFI, PIPEDA).
Understand how the Bank’s risk appetite and risk culture should be considered in day-to-day activities and decisions
Product Vision, Backlog and Project Management
Develop and champion the vision and roadmap for assigned data products, aligning them with overall business objectives
Translate business requirements into clear, concise, and actionable user stories and acceptance criteria
Collaborate with technical teams to develop project plans, monitor progress, and address issues.
Maintain and prioritize a product backlog, ensuring it reflects the most valuable and feasible features for development
Stakeholder Management
Build and maintain strong relationships with stakeholders across various business units, technical teams, and executive leadership
Effectively communicate product updates, progress, and challenges to stakeholders
Investigate and resolve data quality issues, working closely with stakeholders
Performance Measurement & Optimization
Define key performance indicators (KPIs) and metrics to measure data product success
Monitor data risk metrics from the Enterprise Risk Appetite Framework and address early warnings to ensure compliance.
Conduct data mapping, and data reconciliation exercises
Identify, promote, and lead opportunities to improve the efficiency and effectiveness of procedures, including streamlining, automating, and standardization
Proactively identify and address any roadblocks to product delivery and user adoption
Leadership & Mentorship
Provide guidance, support, and coaching to team members
Foster a collaborative, productive, and positive team environment
Do you have the skills that will enable you to succeed in this role? We'd love to work with you if you have:
Post-secondary education in Computer Science, Engineering, Data Science, Business or a related field; Master’s degree preferred
Several years of experience in data product management or related fields
Proven experience in defining delivering successful data products in complex environments
Strong understanding of data management concepts, including data governance, data warehousing, data lakes, and data security
Experience with agile development methodologies (e.g., Scrum, Kanban)
Excellent communication, interpersonal, and presentation skills
Ability to translate complex technical concepts into clear and understandable business language
Strong analytical and problem-solving skills
Experience with data visualization tools (e.g., Looker, Tableau, Power BI)
Familiarity with cloud-based data platforms (e.g., AWS, Azure, GCP)
Experience with Data Management and Issue Management tools such as Collibra
Demonstrated ability to lead and influence cross-functional teams
Experience working in a regulated industry, particularly the Canadian financial services sector, is a significant asset
Strong understanding of Canadian regulatory requirements (e.g., PIPEDA, OSFI)
Experience building automated solutions to support reporting and analytics functions
Experience with data mesh implementation is a strong asset
Professional experience with modern ML tooling is an asset (e.g., Scikit-learn, XGBoost, TensorFlow, PyTorch, Spark ML, etc.)
A strong understanding of data management principles, product ownership best practices, and the Canadian financial services landscape
Comfortability working in a hybrid work environment
Location(s): Canada : Ontario : Toronto
Scotiabank is a leading bank in the Americas. Guided by our purpose: "for every future", we help our customers, their families and their communities achieve success through a broad range of advice, products and services, including personal and commercial banking, wealth management and private banking, corporate and investment banking, and capital markets.
At Scotiabank, we value the unique skills and experiences each individual brings to the Bank, and are committed to creating and maintaining an inclusive and accessible environment for everyone. If you require accommodation (including, but not limited to, an accessible interview site, alternate format documents, ASL Interpreter, or Assistive Technology) during the recruitment and selection process, please let our Recruitment team know. If you require technical assistance, please click here. Candidates must apply directly online to be considered for this role. We thank all applicants for their interest in a career at Scotiabank; however, only those candidates who are selected for an interview will be contacted.