Senior Data And AI Platform Engineer

Job Description Job ID: PRJ-DXB-245

Department: Product Development

Job Type: Permanent

Location: Dubai

Job Details

We are looking for a Senior Data & AI Platform Engineer with strong expertise in data architecture, database design, and scalable system development. The ideal candidate should have a deep understanding of data engineering concepts, modern data platforms, and the ability to design robust, scalable backend systems and data pipelines.

Key Responsibilities Key Responsibilities

• Design and develop scalable backend systems
• Define and implement data architecture and database design strategies
• Build and optimize data ingestion and transformation pipelines
• Develop and maintain unified data models across multiple systems
• Design end-to-end data flows and integration strategies
• Collaborate with cross-functional teams to ensure efficient data handling and processing
• Ensure system scalability, performance, and reliability

Machine Learning & AI Integration

• Work closely with the AI/ML team to understand data requirements for model training, feature engineering, and pipeline development
• Prepare, validate, and deliver clean, structured data to support AI/ML systems and intelligent workflows
• Consume and integrate outputs from ML models into data pipelines and backend systems
• Maintain awareness of ML concepts to effectively collaborate with AI/analytics teams

Core Technical Skills

• Backend & System Design
• Expertise in system scalability and performance optimization
• Solid understanding of distributed systems and backend architecture
• Data Engineering Concepts (IMPORTANT)
• Strong knowledge of data modelling (OLTP vs OLAP)
• Strong knowledge of data lake architecture (primary) and data warehousing concepts
• Strong knowledge of REST APIs and API design (FastAPI / Flask / Django)

Core Platforms & Technologies (Required)

Strong Working Knowledge Of

• Relational databases - strong hands-on experience required (e.g. PostgreSQL, MS SQL Server, MySQL)
• Non-relational / NoSQL databases - working knowledge required (e.g. MongoDB, SQLite, TimescaleDB, Redis)
• Graph databases - understanding of graph data models (e.g. Apache AGE, Neo4j concepts)
• Comfortable working across multi-database environments - relational, time-series, graph, and cache layers in a single architecture

Good to Have: Hands-on experience with modern data tools such as Kafka, Airbyte, S3/ADLS, Snowflake, or similar platforms

Data Ingestion & Processing

Ability To Design And Implement

• Data ingestion pipelines
• Data transformation layers (ETL/ELT)
• Unified and scalable data models
• System Thinking & Architecture

Ability To

• Design scalable backend architectures
• Define and manage data flow across systems
• Guide integration strategies between multiple services and platforms

Good to Have

• Experience with cloud platforms (AWS / GCP / Azure)
• Exposure to real-time data processing systems
• Knowledge of ML data pipelines or analytics workflows
• Experience using Python for data ingestion pipelines, transformation scripts, and automation workflows is an advantage

What We’re Looking For

• Passion for experimenting with new tools, frameworks, and ideas
• Ability to quickly prototype and iterate on features
• Interest in blending creativity with engineering
• Comfort working in less rigid, exploratory development environments
• Strong curiosity and self-learning mindset

Bonus Points If You

• Use AI-assisted coding tools (like GitHub Copilot, Cursor, Antigravity, Claude)
• Build side projects, prototypes, or experimental apps
• Enjoy rapid MVP development, or creative coding
• Stay updated with latest trends in AI, and developer tools

Requirements (Qualifications/Experience/Competencies) Bachelor's degree in Computer Science, Informat