I am hiring for the below role for one of my clients in Abu Dhabi. For more information, please contact me. The customer would like to speak to candidates straight away.

Job Title – VP Of Data – (Director Grade internally)

Salary – AED 80,000 – AED 85,000 Per Month

Perm Role

Location – Abu Dhabi

Start Date – TBC

Full Package

• Education Allowance – AED 40,000 Per Child (Up to 3 Kids)
• Flights home (Full Family)
• Bonus – Up to 4 full fixed + other statutory benefits
• Company to provide Flights and Accommodation for 1 month for people relocating

Reports To: Chief Executive Officer

Department: Data Department (Platforms & Analytics)

Role Purpose: To lead a newly internal data organization within my client current existing organisation, encompassing data engineering, data product development, and data governance. The role’s purpose is to establish a robust data platform and analytics capability for the client– enabling data-driven decision making, advanced analytics, and AI/ML initiatives. This executive defines the data strategy, oversees the building of data infrastructure and products, and ensures data quality, governance, and compliance. To serve as the champion for treating data as a strategic asset and delivers platforms and services that transform raw data into actionable insights and innovative data products.

Experience & Education Requirements:

• Experience: 12+ years of experience in data-focused roles. This should include substantial experience (5+ years) in leading data engineering or analytics teams, preferably at an enterprise level or in a large-scale data environment.
• A successful track record of implementing data platforms or large analytics programs is required. Experience should also show ability to interface with business leadership – e.g., presenting data strategy or running data innovation workshops.
• Education: Bachelor’s degree in computer science, Data Science, Information Systems, or related field (required). Master’s or PhD in Data Science, Information Management, or MBA with a technology focus (preferred).

Key Responsibilities:

• Data Strategy & Architecture: Define data strategy and target state architecture for data platforms (covering data lakes, warehouses, pipelines, and analytics/ML platforms). Set the vision for how data is collected, stored, managed, and used across the customers businesses, ensuring scalability, security, and alignment with enterprise architecture principles

• Data Platform Development: Oversee the design and development of core data infrastructure – including cloud-based data lakes/warehouses, ETL/ELT pipelines, real-time streaming systems, and analytics tools. Ensure that the data engineering team delivers a high-performance platform that serves multiple use cases (BI reporting, advanced analytics, machine learning) and is well-integrated with the businesses other systems and solutions.

• Data Governance & Quality: Implement a robust data governance framework in conjunction with the Data Governance team. Establish policies and standards for data quality, metadata management, master data management, and acces controls. Ensure compliance with relevant data protection regulations (e.g., GDPR) and internal policies, minimizing risk related to data security and privacy

• Budget & Talent Management: Manage the budget for the data division, including investments in technology and personnel. Build and grow a high-caliber data team by attracting top talent in data engineering, data science, and governance. Mentor department heads (Data Engineering, Data Products, Data Governance) and ensure the team structure and skills remain aligned with evolving business needs

Required Technical Competencies:

• Data Management (DATM) – Level 6: Mastery in governing and controlling organizational data assets – ensuring integrity, availability, and security of data across systems. Ability to set data standards and lifecycle policies at an enterprise level

• Data Engineering (DENG) – Level 6: Expertise in designing and implementing complex data pipelines, integration architectures, and storage solutions (relational and NoSQL databases, big data platforms) Capable of leading teams in modern data engineering practices (cloud-based, distributed processing).

• Data Science & Analytics (DATS/INAN) – Level 5: Strong understanding of analytics and machine learning techniques. While not necessarily coding models, able to guide data scientists in choosing the right methods and validate that analytical approaches align with business goals.

• Enterprise & Data Architecture (STPL & DTAN) – Level 5: Proficient in aligning data architecture with overall enterprise architecture. Knowledge of data modelling and design principles (conceptual, logical, physical data models) to ensure cohesive data structures across the organization.

• Governance (GOVN) – Level 5: Capability to implement governance frameworks – setting up data stewardship, policy enforcement, and audit processes. Ensures compliance with data-related regulations and internal governance standards

Tools, Platforms & Certifications:

• Tools/Platforms: Extensive experience with modern data tech stack: distributed data processing (Hadoop/Spark), data warehouse and Lakehouse solutions, ETL/ELT tools (Azure Data Factory, Apache NiFi, etc.), and real-time streaming (Kafka, Apache Flink).
• Proficient in SQL and at least one programming language for data (Python, Scala).
• Familiar with analytics platforms (Power BI, Tableau) and ML platforms (Azure ML, TensorFlow).