Data Lead

CSC Generation

. Own the analytical layer between raw data and business decisions .

Posted 10/22/2026full-timeToronto • CanadaSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in SQL and Python for data analysis, modeling, and validation, while leveraging AI tools to enhance analytical workflows. Proficient in integrating data across systems and aligning metrics to support business decision-making.

Highest-signal resume keywords

SQL ProgrammingPython ProgrammingData ModelingCloud Data WarehousingBusiness Intelligence Tools

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLPythonData ModelingData ValidationETL/ELT PipelinesData GovernanceKPI DefinitionAI ToolsSemantic Layer DesignData Integration

Soft Skills

Business AcumenAnalytical ThinkingCollaborationCommunication

Tools & Technologies

BigQuerySnowflakeRedshiftLookerTableauPower BIGoogle AnalyticsNetSuiteAirflow

Industry Keywords

E-CommerceRetail AnalyticsMarketing AnalyticsAI-Assisted Analytics

Tech Stack

Tools & technologies

AirflowAmazon RedshiftBigQueryCloudERPETLPythonSQLTableau

About the role

Key responsibilities & impact

Own the analytical layer between raw data and business decisions
Write, review, and debug SQL and Python code, including AI-generated code
Build and maintain analytical data models across the portfolio
Design and maintain semantic layers and reusable BI data models
Integrate and reconcile data across systems and business units
Align metric definitions and master data for customers and products
Validate data and reconcile discrepancies across ERP, web analytics, and other sources
Scope technical feasibility, effort, trade-offs, and delivery expectations for data requests
Define KPIs and translate business questions into analytical approaches
Provide clear, actionable recommendations
Use AI tools such as Claude Code and Codex to accelerate analysis, coding, and documentation
Critically review AI-generated outputs
Partner with data engineering, business stakeholders, and external vendors
Maintain data quality across the portfolio
Deliver reconciled cross-brand metrics, reusable BI-layer data models, and accelerated analytics workflows

Requirements

What you’ll need

Strong SQL and Python skills, including writing, reviewing, and debugging AI-generated code
Experience with cloud data warehouses such as BigQuery, Snowflake, or Redshift
Experience with data modeling
Familiarity with ERP and web analytics data sources such as NetSuite and Google Analytics
Understanding of ETL/ELT pipelines, data warehousing, and orchestration tools such as Airflow
Experience integrating and reconciling data across multiple systems or business units
Experience aligning metric definitions and master data
Rigorous data validation and governance skills
Proficiency with at least one modern BI tool such as Looker, Tableau, or Power BI
Experience building semantic layers or reusable data models
Fluency with AI coding and analysis tools
Strong business acumen and experience defining KPIs
Ability to translate business questions into analytical approaches
Ability to partner with data engineering, business stakeholders, and external vendors
Mandatory in-person interview attendance before an offer
Valid LinkedIn profile URL, or credible explanation and alternative professional-background evidence if no profile exists
Employment contingent on a background check, including verification of prior employment dates
Preferred: foundation in statistics and experimentation, experience with AI-assisted analytics workflows, and experience in e-commerce, retail, or marketing analytics

Benefits

Comp & perks

Paid time off policies
RRSP match
Medical coverage
Dental coverage
Vision coverage
Supplemental benefit options
Employee discounts across the portfolio of brands
AI-first skill building
Cross-functional impact across the portfolio
End-to-end ownership