Sr. Data Analyst to support the asset management data platform team for a large insurance client - 5322

Sr. Data Analyst to support the asset management data platform team for a large insurance client - 5322

You will be responsible for data analysis, data mapping, data modeling, governance and testing of various data sources and platforms. You will also collaborate with other data analysts, engineers, and business stakeholders to create derived consumable data products. This role includes thorough analysis and understanding of capital markets data so a strong background in Asset Management/Capital Markets is required. Proficient facilitation, interpersonal and elicitation skills are also imperative to capture complex business/data requirements in this fast-paced environment.

Duration: 1 year (possibility of extension)

Location: Hybrid 3 days/week (Toronto, Waterloo)

Must haves:

• 8+ years of experience in data analysis, data modeling, data governance, or data engineering.
• 5+ years of experience in Asset Management and/or capital markets with strong/broad domain knowledge of investment instruments and the asset management business.
• Experience with technologies such as SQL, Python in cloud (AWS) environments
• Experience with Agile delivery model tools (e.g., Jira; confluence; Miro)

Nice to haves:

• Bachelor's degree in data science, computer science, statistics, mathematics, or training in related field.

Job Responsibilities:

• Perform data mapping and data modeling activities to ensure data quality and integrity across different data sources and platforms.
• When establishing new data products, define, develop and implement the component defined within the data certification process.
• Adhere to, enhance and support governance policies and procedures by ensuring data attributes are clearly defined and data security, privacy, and compliance requirements are met.
• Support Data Owners/Steward in resolving technical data-related issues using specialized skills and tools.
• Conduct data/process testing and validation to identify and resolve issues and anomalies.
• Analyze and interpret data using various tools and techniques to generate insights and recommendations for business stakeholders.
• Define and clearly articulate problem statements while communicating and presenting data insights/recommendations to various audiences, both technical and non-technical.
• Manage discussions, negotiations and conflicts through resolution, using communication strategies that align with various audience styles and cultures.