About Khazna

Khazna launched in 2020 with a mission to improve the financial well-being of the underbanked, who have little access to formal financial services, by providing access to convenient, effective, and secure smartphone-based financial services. Khazna has received the Central Bank of Egypt’s first prepaid card license and aims to become the go-to neobank for underbanked consumers across the Middle East. In the next phase of its journey, Khazna is looking to continue scaling up its operations in Egypt and to launch its operations in Saudi Arabia.

This is a fun stage in the company's lifecycle, as the core foundation has been but it is still early enough to assume a ton of ownership and to help shape the future of the company and its success.

About the role

Own the structure, reliability, and usability of Khazna’s data layer in Egypt and KSA. Convert fragmented operational data into a governed, scalable data model that supports decision-making, growth, and product monetization. Eliminate metric ambiguity, enforce a single source of truth, and enable business teams to operate independently through analytics.

Core Responsibilities

1) Data Modeling & Architecture

• Design and maintain scalable data models (fact/dimension, star/snowflake schemas) aligned with business use cases
• Define canonical datasets for core domains (users, transactions, lending, payments, risk, engagement)
• Standardize metric definitions and enforce consistency across teams
• Own logical data model design and schema definitions; partner with Data Engineering on physical data warehouse implementation and evolution

2) Business Analytics Enablement

• Translate business questions into structured datasets and dashboards
• Build and own executive dashboards (growth, retention, revenue, risk)
• Enable self-serve analytics for product, growth, finance, and operations teams
• Drive cohort analysis, funnel analysis, LTV, CAC, and unit economics frameworks

3) Data Governance & Quality

• Define data ownership across teams
• Establish validation, monitoring, and anomaly for business data; partner with Data Engineering for monitoring and enforcement
• Maintain documentation for datasets, pipelines, and definitions
• Ensure compliance with data privacy and regulatory requirements

4) Cross-functional Leadership

• Partner with Growth, Marketing, Operations, Product, Risk, and Finance to align on data needs
• Act as the gatekeeper for metric definitions and reporting standards
• Prioritize analytics roadmap based on business impact
• Mentor analysts and build a high-leverage data team

5) Data Pipeline Awareness

• Collaborate with data engineers on pipeline design and performance
• Understand ETL/ELT workflows, data ingestion, and transformation logic

Required Skills:

Technical

• Strong SQL
• Deep understanding of data modeling principles (dimensional modeling, normalization vs denormalization)
• Experience with data warehouses (BigQuery, Snowflake, Redshift or equivalent)
• Hands-on experience with BI tools (Tableau, Looker, Power BI, Metabase)
• Experience building analytical datasets and dashboards at scale

Analytical

• Strong business intuition (growth, fintech, lending, risk preferred)
• Ability to define and standardize KPIs across teams
• Experience with cohort analysis, funnel optimization, and experimentation

Leadership

• Proven experience managing analysts or data teams
• Ability to enforce structure in ambiguous environments
• Strong stakeholder management across technical and non-technical teams

Nice to Have

• Hands-on experience with data engineering concepts (ETL pipelines, data ingestion, streaming)
• Experience working in fintech, lending, or regulated environments
• Familiarity with event-driven architectures and product analytics tracking
• Experience implementing data governance frameworks from scratch

Success Metrics

• Single source of truth established across all core business metrics
• Reduction in conflicting reports and metric discrepancies
• Adoption of self-serve dashboards across business teams
• Improved decision speed and quality across growth and product
• Scalable, documented, and reliable data models supporting all analytics needs