Knya - Lead - Data & AI

Role Overview:

We're looking for a high-ownership Lead - Data & AI to build and own Knya's end-to-end data ecosystem that powers business decisions across ecommerce, retail, marketing, supply chain, finance, and customer experience.

Today, our business data lives across multiple platforms including Shopify, ERP, POS, CRM, marketplaces, and marketing tools. This role will bring these data sources together into a unified data platform, enabling real-time insights, automation, forecasting, and AI-driven decision making.

You will work closely with founders and business leaders to build a scalable data foundation that improves operational efficiency, customer understanding, inventory planning, and business performance.

Key Responsibilities:

Data Strategy & Architecture:

• Define and own Knya's enterprise data strategy.
• Build a centralized data ecosystem connecting Shopify, ERP, POS, CRM, marketplaces, finance, warehouse, and marketing platforms.
• Design scalable data models and pipelines for reporting and analytics.
• Ensure high standards of data quality, governance, security, and documentation.

Data Engineering & Integration:

• Integrate data across all internal and external systems through APIs and ETL pipelines.
• Build reliable automated data pipelines.
• Ensure data availability for reporting, analytics, and AI use cases.
• Improve data consistency across business functions.

Business Intelligence & Analytics:

• Build dashboards using Power BI, Looker, Tableau, or Metabase.
• Develop KPIs across Sales, Marketing, Supply Chain, Finance, Retail, and Customer Experience.
• Enable self-service analytics.
• Deliver actionable insights.

Customer & Marketing Analytics:

• Create a unified customer view across online and offline channels.
• Build segmentation using RFM, CLTV, cohorts, and behavioral data.
• Support personalization, loyalty, and retention.
• Measure campaign performance and attribution.

AI & Advanced Analytics:

• Build predictive models for demand forecasting, inventory planning, churn, CLTV, and recommendations.
• Implement AI tools to automate reporting and decision-making.

Leadership & Stakeholder Management:

• Partner with business teams.
• Manage external data engineering and BI partners.
• Drive a data-first culture.