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CSC Generation is an AI-native holding company transforming omnichannel retail through its Genesis operating platform. The company owns 13 iconic brands including Sur La Table, Backcountry, and One Kings Lane, generating $1B+ in revenue across distinct ERPs, web analytics platforms, and operational systems.
As Senior Analytics Engineer, you will own the analytical layer bridging raw data and business decisions across the entire portfolio. You'll build trusted, reconciled data assets that business teams can act on confidently, modeling data, defining metrics, building semantic layers, and partnering with stakeholders to translate ambiguous questions into clear, validated answers. Success in the first 6–12 months means delivering reconciled cross-brand metrics, establishing reusable data models in the BI layer, and demonstrating measurable acceleration of analytics workflows through AI tooling.
Key Responsibilities:
- Write, review, and debug SQL and Python code—including AI-generated code—to build and maintain analytical data models across the portfolio
- Design and maintain semantic layers and reusable data models in BI tools (Looker, Tableau, Power BI) 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 (customers, products)
- Validate data rigorously, identifying plausible-but-wrong results and reconciling discrepancies across ERP, web analytics, and other sources
- Scope technical feasibility, effort, and trade-offs for new data requests; set realistic delivery expectations
- Define KPIs and translate business questions into analytical approaches with actionable recommendations
- Leverage AI tools (Claude Code, Codex) to accelerate analysis, coding, and documentation while critically reviewing outputs
- Partner with data engineering, business stakeholders, and external vendors to deliver insights and maintain data quality
This is a lean team with end-to-end ownership: you own the full path from raw data to trusted business metric, moving fast and making decisions independently.
Required Qualifications:
- Strong SQL and Python skills; ability to write, review, and debug code efficiently, including AI-generated code
- Experience with cloud data warehouses (BigQuery, Snowflake, Redshift) and data modeling
- Familiarity with ERP and web analytics data sources (NetSuite, Google Analytics)
- Solid understanding of ETL/ELT pipelines, data warehousing, and orchestration tools (Airflow)
- Experience integrating and reconciling data across multiple systems or business units, including aligning metric definitions and master data
- Rigorous approach to data validation and governance with strong instinct for identifying inaccurate results
- Proficiency with at least one modern BI tool (Looker, Tableau, Power BI), including building semantic layers or reusable data models
- Fluency with AI coding and analysis tools, with judgment to critically validate outputs
- Strong business acumen with experience defining KPIs and translating business questions into analytical approaches
- Proven ability to partner with data engineering, business stakeholders, and external vendors, setting realistic expectations
Preferred Qualifications:
- Solid foundation in statistics and experimentation (A/B testing, hypothesis testing)
- Experience building AI-assisted workflows or enabling teams to adopt AI tools for analytics
- Experience in e-commerce, retail, or marketing analytics (affiliate, attribution)
