Data Lead; Costa Rica)

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 – Costa Rica

CSC Generation’s portfolio spans 13 brands, each generating data across distinct ERPs, web analytics platforms, and operational systems. This role exists to bridge those sources — building trusted, reconciled data assets that business teams can act on confidently.

As Senior Analytics Engineer , you will own the analytical layer between raw data and business decisions: modeling data, defining metrics, building semantic layers, and partnering with stakeholders to turn ambiguous questions into clear, validated answers. 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.

This is a lean team. You will own a lot, move fast, and make decisions with full end-to-end responsibility.

• 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.

• 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., Big Query, Snowflake, Redshift) and data modeling.
• Familiarity with ERP and web analytics data sources (e.g., Net Suite, 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.
• Rigorous approach to data validation and governance with a strong instinct for identifying inaccurate results.
• Proficiency with at least one modern BI tool (e.g., Looker, Tableau, Power BI), including building semantic layers or reusable data models.
• Fluency with AI coding and analysis tools, with the judgment to critically validate their 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…