Head of Data

Role Overview

Head of Data at Ziina, a fintech and payments company based in the UAE. This is a founding leadership role to build and lead a new Data team from the ground up.

Company Overview

Ziina is at a major inflection point in growth with rich payments data, a strong platform foundation, and a founding team of data platform and AI engineers already in place. The company operates as a licensed financial institution.

Role Purpose

Define and execute the vision, strategy, and roadmap for data, ML, and AI across Ziina. Build self-serve platforms and governance frameworks that enable every team—Product, CX, Business Development, Finance, and Fincrime—to ship AI-powered use cases safely and measurably. Scale the Data function from a small founding team into a trusted platform that the whole organization uses.

Key Responsibilities

Strategy & Vision

• Define and own the vision, strategy, and roadmap for data, ML, and AI at Ziina, focusing investment where it creates the most value across product and operations.

Data Foundations

• Evolve the existing data foundations: a trusted, well-modeled warehouse and semantic layer with clear ownership, quality checks and lineage, so data is easy for both people and AI agents to find, understand and use.

Platform & Tools

• Build the self-serve ML, LLM, agent and experimentation platforms that let every team at Ziina put AI to work safely and measurably.

Team Leadership

• Lead, grow, and mentor the Data team, starting with our data platform engineers and AI engineer, and hire the next wave of engineers and scientists as we scale.

Governance & Compliance

• Establish AI and model governance in line with regulatory expectations for licensed financial institutions, including model risk management, monitoring, bias testing, explainability, and human oversight.

Cross-Functional Partnerships

• Partner with every function including Product, Fincrime, CX and Finance to find high-impact use cases, ship the first versions alongside them, and turn what works into repeatable, self-serve tools.

Qualifications & Experience

• 8+ years of experience in data, ML, or AI engineering.
• 3+ years leading teams that shipped ML or AI systems to production.
• Built or run core ML platform infrastructure including feature stores, training pipelines, model registries, real-time serving, and monitoring, with clear understanding of build-vs-buy tradeoffs at startup scale.
• Shipped LLM-powered products or internal tools to production, with hands-on experience in evals, prompt iteration, retrieval, and model routing or cost optimization.
• Hands-on experience with agent frameworks and tool-use protocols such as MCP, with a clear point of view on giving agents access safely.
• Deep understanding of experimentation, including experiment design, statistical power, guardrail metrics, and the common ways A/B tests mislead.

Skills & Competencies

• Hands-on proficiency in Python and SQL.
• Comfortable reviewing designs and building alongside a small team.
• Able to translate technical work into business outcomes and influence leaders in non-technical teams.
• Based in, or open to relocating to, the UAE.

Additional Information

Preferred Experience

• Proven experience building data and AI platforms at a fintech, payments company, or other regulated, high-throughput business.
• Track record of taking a Data function from zero (or near-zero) to a platform used across the company.
• Production ML experience in payments, such as fraud, risk, forecasting, personalisation, or merchant intelligence.
• Hands-on experience with model risk management and AI governance under a financial regulator.
• Experience building AI products for Arabic-speaking users or MENA markets.
• Active engagement in the tech community through open source contributions, conference speaking, or technical writing.

Technology Stack

• Backend: TypeScript, Node.js, Nest.js.
• Frontend: Next.js, React, TypeScript.
• Mobile: Swift/SwiftUI for iOS; Kotlin for Android.
• Storage & Search: PostgreSQL, Redis, Elasticsearch.
• Data Stack: Snowflake for data warehouse, dbt for transformations, Metabase for BI.