Senior Data Analyst

Job Title Senior Data Analyst

MUST HAVE

• Bachelors degree in Data Science, Information Systems, Computer Science, Business Analytics, or a related field
• Strong experience supporting data mapping, data modeling, or data migration initiatives
• Proficiency in:
• SQL (intermediate to advanced)
• Data analysis and profiling techniques
• Excel or equivalent analytical tools
• Data visualization tools (Power BI)
• Solid understanding of relational databases, structured data, and data integration patterns
• Ability to interpret, document, and communicate data transformation logic clearly
• Strong written and verbal communication skills

Engagement Details

• Contract Start Date: February 2, 2026
• Contract End Date: August 10, 2026

Location

• City: Toronto, Ontario

Additional Information

• Closing Date: January 26, 2026 – 12:00 PM

Role Overview

The Senior Data Analyst will support the Data Platform team in designing, mapping, validating, and documenting enterprise data solutions that enable reliable, secure, and scalable cloud and data infrastructure. This role plays a critical function in ensuring data accuracy, governance, and alignment between business requirements and technical implementation across Azure-based data ecosystems.

The Data Platform environment includes Azure, Databricks, GitHub, Data Warehouses, ETL processes, data pipelines, advanced analytics, reporting, and data visualization. This capability underpins enterprise-wide technology and customer-facing solutions.

Key Responsibilities

Data Mapping & Documentation

• Lead detailed data mapping activities across source systems, data platforms, and target destinations
• Document field-level mappings, transformation rules, data lineage, and business logic
• Ensure alignment with enterprise data standards, governance policies, and architectural patterns
• Maintain clear, version-controlled mapping specifications for engineering teams
• Analyze and profile datasets to assess structure, relationships, data quality, and anomalies
• Validate mapped data against business processes and stakeholder expectations
• Identify data gaps, inconsistencies, and migration or integration risks

Stakeholder Collaboration

• Collaborate with data engineers, architects, business analysts, product owners, and SMEs to gather and clarify requirements
• Translate business definitions into technical mapping and documentation artifacts
• Facilitate working sessions and workshops to resolve data ambiguities and align on business rules

Data Quality & Validation

• Support testing teams by defining validation rules and expected transformation outputs
• Perform data reconciliation between source and target systems
• Partner with data governance teams to improve data integrity, metadata accuracy, and documentation quality

Reporting & Insights

• Develop dashboards, reports, and analytical outputs to support business needs
• Present findings, insights, and recommendations to both technical and non-technical stakeholders
• Contribute to standardized reporting frameworks and self-service analytics capabilities

FSIN