Data Designer

Job Overview: Data Designer

As a Data Designer at TD, you will provide expert guidance and leadership in data-related initiatives, ensuring data quality, governance, and effective data solutions across various business segments. This role involves significant collaboration with business and technology teams, focusing on data impact assessments, risk mitigation, and the implementation of data information management standards.

You will be instrumental in developing and maintaining knowledge of available data sources, identifying critical data elements, and ensuring compliance with enterprise data standards. A key aspect of this position is performing data profiling, resolving data issues, and driving knowledge transfer activities to empower business teams with robust information management solutions.

Key Responsibilities:

Customer Focus

• Provide expert guidance on data impact assessments and data risk mitigation for projects.
• Implement data information management standards and ensure data quality requirements are met.
• Develop knowledge of upstream data sources and platforms.
• Identify critical data elements to support Business Segment data governance.
• Ensure data retention and disposal comply with enterprise standards.
• Perform data profiling using TD tools and ad hoc system query languages.
• Support the data lifecycle, resolve data issues, and assist users in data interpretation.
• Investigate root causes of data issues and ensure resolution with prototyping solutions.
• Define knowledge transfer activities to support business teams.
• Adhere to enterprise data frameworks and methodologies.
• Ensure business operations comply with internal and external requirements.
• Collaborate with business partners and stakeholders for project success.
• Document business data requirements through research and analysis.
• Participate in cross-functional initiatives as a subject matter expert.
• Conduct meaningful analysis to draw conclusions and make recommendations.
• Stay updated on emerging issues, trends, and regulatory requirements.
• Promote a culture of risk management and control.

Shareholder Value

• Collaborate with technology and business teams for successful data solution delivery.
• Facilitate data analysis and investigations for business users and QA teams.
• Provide oversight on business impact post-implementation during the warranty period.
• Coordinate business requirements with technical teams, ensuring smooth data integration.
• Lead or participate in business and technical design reviews for data architectures.
• Raise and manage change requests in collaboration with stakeholders.
• Lead initiatives on data governance and data management.
• Ensure business metadata and data lineage are documented and integrated.
• Adhere to and promote best practices for data security.
• Document business requirements and technical decisions effectively.
• Safeguard organizational interests, managing risks and ensuring compliance.
• Stay current on industry trends and expand knowledge of data tools.
• Enable cross-functional collaboration and knowledge sharing.

Employee / Team Engagement

• Participate actively as a team member, fostering a positive work environment.
• Provide thought leadership and industry knowledge, facilitating knowledge transfer.
• Stay current on emerging trends and developments, growing business knowledge.
• Engage in personal performance management and development, including cross-training.
• Keep teams informed on project status and day-to-day activities.
• Contribute to team skill development through mentorship and best practices.
• Lead and develop relationships with internal and external partners.
• Contribute to a fair, positive, and equitable diverse workforce.
• Act as a brand ambassador for your business area and TD.

Qualifications & Experience:

• Undergraduate degree or Technical Certificate with 3+ years of relevant experience in business administration, statistical, mathematical, scientific, or financial background.
• 3+ years of data engineering experience, particularly with big data technologies, preferably Azure.
• Excellent SQL skills for data querying, profiling, transformation, analysis, and data modeling.
• Hands-on experience with the Azure ecosystem, including Azure Data Lake Storage, Azure Data Factory, and Synapse.
• Proficiency in Python and PySpark.
• Highly analytical mindset, critical thinking, and strong problem-solving abilities.
• Ability to solve complex problems by analyzing multiple upstream and downstream sources.
• Experience in the Insurance Domain is an asset.

Key skills/competency:

• Data Governance
• Data Quality
• SQL
• Azure Data Lake Storage
• Azure Data Factory
• Azure Synapse
• Python
• PySpark
• Data Modeling
• Data Profiling