Role: Data Analyst
Location: Toronto (Hybrid)
Duration: 6-12 Months

Job Description:
Data Discovery & Analysis

• Analyze all Netezza database tables to identify:
• Business-critical and frequently used tables
• Redundant and unused data assets
• Perform data profiling and quality analysis to understand structure, patterns, and anomalies
• Assess data dependencies and relationships across systems
• Migration Assessment (Netezza → Azure)

Evaluate and report:

• Number of tables already migrated to Azure
• Tables pending migration
• Validate data consistency between Netezza and Azure environments
• Support migration planning through impact analysis
• Data Mapping & Lineage
• Create source-to-target data mapping documents
• Establish end-to-end data lineage across systems
• Document transformations and business rules applied during migration
• Metadata & Documentation

Develop and maintain:

• Metadata repository / definition documents
• Data dictionary / taxonomy (asset library)
• Table-level and column-level documentation
• Ensure alignment with enterprise data governance standards
• Data Modeling
• Perform data modeling and mapping activities

Create:

• Conceptual, logical, and physical data models
• Domain-based models for retail or business-specific datasets

Design models optimized for:

• Analytical workloads
• Enterprise BI and reporting
• Development & Implementation
• Write and optimize SQL queries for data analysis and validation
• Develop DDL scripts and assist in deploying data models across environments
• Perform data wrangling and transformation using Python or similar tools
• Work with data lakes and structured/unstructured data sources

Experience

• 4+ years of experience in data analysis, data modeling, or data engineering roles
• Technical Skills
• Strong expertise in:
• SQL (mandatory)
• Python (or other scripting languages)

Experience with:

• Netezza and cloud platforms (preferably Azure)
• Data modeling tools (e.g., ERwin, ER/Studio, Azure tools)
• Data warehousing and analytical workloads

Solid understanding of:

• Data lineage and metadata management
• ETL/ELT processes
• Data migration strategies
• Data Management Skills
• Data profiling and analysis techniques
• Data mapping and transformation documentation
• Metadata, taxonomy, and data dictionary creation
• Collaboration & Stakeholder Management

Work closely with:

• Data engineers
• BI/reporting teams
• Data science teams
• Business stakeholders
• Gather and translate business requirements into technical data solutions
• Support downstream data marts, semantic layers, and analytics use cases