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CSC Generation is an AI-native holding company that acquires and transforms iconic retail brands using Genesis, its proprietary operating platform. The company manages a portfolio of 13 brands (including Sur La Table, Backcountry, One Kings Lane) generating $1B+ in revenue across distinct ERPs, web analytics platforms, and operational systems.
In this Senior Analytics Engineer role, 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, working in a lean team with full end-to-end responsibility.
Key responsibilities include:
- Writing, reviewing, and debugging SQL and Python code (including AI-generated code) to build and maintain analytical data models across the portfolio
- Designing and maintaining semantic layers and reusable data models in BI tools (Looker, Tableau, Power BI) as the single source of truth for business metrics
- Integrating and reconciling data across multiple systems and business units, aligning metric definitions and master data (customers, products)
- Validating data rigorously to identify plausible-but-wrong results and reconcile discrepancies across ERP, web analytics, and other sources
- Scoping technical feasibility, effort, and trade-offs for business data requests, setting realistic delivery expectations
- Defining KPIs and translating business questions into analytical approaches with actionable recommendations
- Leveraging AI tools (Claude Code, Codex) to accelerate analysis, coding, and documentation while critically reviewing outputs
- Partnering with data engineering, business stakeholders, and external vendors to deliver insights and maintain data quality
Success in the first 6–12 months means delivering reconciled cross-brand metrics that stakeholders trust, establishing reusable data models in the BI layer, and demonstrating measurable acceleration of analytics workflows through AI tooling.
Requirements:
- Strong SQL and Python skills with 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)
- Proven 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 team adoption of AI tools for analytics
- Experience in e-commerce, retail, or marketing analytics (affiliate, attribution)
