Senior Data Product Analyst

SUMMARY 

This Senior Data Product Analyst is a senior role responsible for partnering with business stakeholders to translate strategic needs into clear data and reporting requirements. This role owns the lifecycle of analytical data products – from ideation and design through validation and sustainment. It leads the consolidation of semantic models and front-end logic into a centralized, governed data layer, ensuring consistency and a single source of truth across the organization. This position applies strong conceptual data modeling, critical thinking, and a data product mindset to guide stakeholders, rationalize reports, standardize metrics, and uplift analytics maturity. The analyst enables sustainable self-service, improves data quality, and advances enterprise-wide alignment to a modern Lakehouse and data governance practices.  

ACCOUNTABILITIES 

• Engage with business stakeholders to understand strategic and operational needs and translate requirements into clear data and reporting specifications aligned with enterprise data strategy and provide recommendations on measurement, and adoption as needed. 

• Own the end-to-end lifecycle of analytical data products (vision, backlog, roadmap, release, maintenance), including defining product key performance indicators (KPIs) and tracking adoption/value. 

• Lead report development and semantic standardization – design/build dashboards and analytical data products, migrate front-end logic into a governed semantic layer, and define conceptual/logical data models to standardize entities, metrics, and hierarchies for a single source of truth. 

•  Collaborate with data engineering to design and validate data structures within the Lakehouse, ensuring that transformations are performed in the platform.  

• Define and maintain standardized KPI definitions, business rules, and metric logic, and prepare clear documentation of these requirements and semantic structures. 

• Conduct data profiling, validation, and reconciliation to ensure data accuracy, quality, and fitness for purpose. 

• Promote and champion data product thinking across the organization, guiding business partners on appropriate request scoping, measurement, and reuse of standardized data assets.  

• Influence and operationalize data governance – lead metric rationalization, shape rules for definitions and semantic assets, and ensure adherence to privacy/security/quality standards. 

• Apply visualization and UX best practices to create clear, intuitive, and insight-driven analytical experiences.  

• Champion data literacy and enablement by mentoring business users, facilitating training, and supporting adoption of self‑service analytics practices, providing functional/ practice guidance.  

JOB REQUIREMENTS 

• 5 or more years progressive experience in business intelligence, data analysis, data product development, or related fields that combine stakeholder engagement with analytical delivery.  

• Expertise and hands-on experience in cloud analytics platforms preferably Microsoft Azure Synapse, Databricks, Azure Data Factory including Data Flow, GIT-based version control, and SQL Server. 

• Demonstrated experience gathering, clarifying, and translating business requirements into actionable data specifications, metric definitions, and analytical product requirements 

• Hands‑on experience developing analytical data products or dashboards using modern BI and analytics tools (e.g. Power BI). 

• Proficiency in DAX, Power Query, and SQL and experience validating, profiling, and interpreting data from relational databases or cloud data platforms. 

• Strong capability in conceptual and logical data modeling, including defining business entities, relationships, hierarchies, and metric logic. 

• Understanding of modern data platform concepts (e.g. ETL/ELT, multi-hop architecture, curated layers, governed data marts) and ability to collaborate effectively with data engineers.  

• Strong analytical, critical thinking, and problem‑solving skills, with the ability to challenge assumptions, evaluate data needs, and guide the organization toward value‑driven analytics. 

• Excellent communication and relationship‑building skills, with demonstrated ability to engage business and technical audiences, facilitate discussions, and influence decision-making. 

• Experience supporting organizational uplift, including mentoring, training, documentation, and the promotion of data literacy and self-service analytics practices.  

• Familiarity with financial services industry regulations and compliance requirements is an asset.  

• Familiarity with predictive analytics or ML‑enabled analytics is an asset. 

EDUCATION 

• Bachelor’s degree in Business/Commerce, Management Information Systems, Computer Science, Data Science, or related analytical or technical field.  

• Certifications in analytics, business analysis, data modelling, or BI tools are considered strong assets.