CSC Generation is the AI-native holding company re-engineering omnichannel retail. We acquire iconic brands and transform them with Genesis, our operating platform combining a Data Fabric, Automation Engine, proprietary tools, and shared services to modernize operations, elevate customer experience, and expand margins. With $1B+ in revenue across 13 brands, our portfolio includes Sur La Table, Backcountry, One Kings Lane, and others that serve as real-world innovation labs.

Reports to: Director of Finance and Business Intelligence

Location: Hybrid – Canada. Toronto, ON preferred

About The Role

What You'll Do

• Write, review, and debug SQL and Python code — including code generated by AI tools — to build and maintain analytical data models across the portfolio.
• Design and maintain semantic layers and reusable data models in BI tools (e.g., Looker, Tableau, Power BI) that serve as the single source of truth for business metrics.
• Integrate and reconcile data across multiple systems and business units, aligning metric definitions and master data such as customers and products.
• Validate data rigorously, spotting results that look plausible but are wrong, and reconciling discrepancies across ERP, web analytics, and other sources.
• Scope and assess technical feasibility, effort, and trade-offs when business teams bring new data requests, setting realistic expectations on delivery.
• Define KPIs and translate business questions into analytical approaches with clear, actionable recommendations.
• Leverage AI tools (e.g., Claude Code, Codex) to accelerate analysis, coding, and documentation while critically reviewing all AI-generated outputs.
• Partner with data engineering, business stakeholders, and external vendors to deliver insights and maintain data quality across the portfolio.

Required Qualifications

• Strong SQL and Python skills, with the ability to write, review, and debug code efficiently, including AI-generated code.
• Experience with cloud data warehouses (e.g., BigQuery, Snowflake, Redshift) and data modeling.
• Familiarity with ERP and web analytics data sources (e.g., NetSuite, Google Analytics).
• Solid understanding of ETL/ELT pipelines, data warehousing, and orchestration tools (e.g., Airflow).
• Experience integrating and reconciling data across multiple systems or business units, including aligning metric definitions and master data.