Analytics Engineer

Role Overview

• Build Gold layer dbt models, including metric-level aggregations, KPI tables, and denormalized summary tables optimized for BI consumption in Sigma.
• Author dbt Semantic Layer metric definitions using MetricFlow, including sell-through, out-of-stock (OOS) rate, conversion rate, average order value (AOV), weeks cover, and other metrics defined in the business metric register.
• Populate and maintain the business glossary for each completed dataset, including metric definitions, calculation notes, known caveats, ownership, and data lineage.
• Participate in business validation sessions with the onshore team and business stakeholders to ensure Gold metrics align with agreed metric register definitions prior to handover to Run operations.
• Author and maintain dbt Explorer documentation, including model descriptions, column descriptions, and metric definitions to ensure the semantic layer remains fully self-documenting.
• Support ongoing Run operations by managing metric change requests, implementing new Gold model additions, monitoring Cortex ML models, maintaining Claude NLQ context updates, and tracking AI agent uptime and performance.
• Collaborate with stakeholders and cross-functional teams to validate business requirements, clarify KPI logic, and ensure consistent metric governance across the platform.

Requirements

• Advanced experience with dbt Semantic Layer and MetricFlow, including metric definitions, dimensions, entities, measures, and time spines.
• Advanced SQL expertise, including metric calculation logic, window functions, ratio metrics, and period-over-period comparisons.
• Basic Python scripting skills for automation and monitoring-related tasks.
• Intermediate experience with Power BI or other self-service BI platforms, with the ability to validate Gold layer outputs within BI environments.
• Intermediate experience with Atlan or similar data cataloguing platforms, including catalogue administration, glossary authoring, and lineage review.
• Strong retail domain knowledge, with a clear commercial understanding of metrics such as sell-through, OOS rate, clearance percentage, return rate, and AOV.
• Strong communication and stakeholder management skills, with the ability to clearly present metric validation findings to non-technical business stakeholders.
• Experience using Claude API or similar AI tooling to translate business metric register rules into dbt Gold model SQL.
• Familiarity with Cortex Analyst YAML generation for scaffolding Semantic Layer definitions aligned with metric register requirements.
• Experience monitoring Cortex ML models, including Forecasting and Anomaly Detection performance, and triggering retraining workflows when necessary.
• Understanding of NLQ (Natural Language Query) context management, including maintaining governance and semantic layer context that supports AI-powered business user interfaces.
• Exposure to LLM APIs, Snowflake Cortex, or similar AI-driven analytics platforms, whether in production, prototype, or personal project environments.

Tech Stack

• Python
• SQL