Data Engineer

Location: Abu Dhabi, UAE
Employment Type: Permanent / Full-Time
Seniority: Mid-Level

Overview

We are seeking a talented Data Engineer to join a growing technology team responsible for building and scaling modern data platforms that power analytics, AI, and business-critical decision-making.

The successful candidate will play a key role in designing, developing, and maintaining high-performance data pipelines and platforms, working closely with Data Scientists, Architects, Product teams, and Technology stakeholders to deliver robust, scalable, and secure data solutions.

This is an excellent opportunity for someone passionate about big data, cloud technologies, and modern data engineering practices.

Key Responsibilities

Data Engineering & Platform Development

• Design, build, and maintain scalable data platforms capable of supporting large-scale analytics and operational workloads.
• Develop robust batch and real-time data pipelines for ingesting, transforming, and processing structured and unstructured data.
• Build and optimise data architectures supporting business intelligence, advanced analytics, machine learning, and AI initiatives.
• Implement data models, lakehouse architectures, and change data capture solutions.
• Develop high-performance systems capable of processing large volumes of data with low latency and high reliability.

Data Operations & Reliability

• Ensure all data pipelines are secure, observable, monitored, and aligned with agreed service levels.
• Implement data quality frameworks, validation rules, lineage tracking, and governance controls.
• Monitor and optimise platform performance, scalability, and operational costs.
• Troubleshoot and resolve production issues across data pipelines and processing platforms.
• Support ongoing improvements to data platform reliability and operational excellence.

Collaboration & Delivery

• Partner with Product, Engineering, Data Science, and Analytics teams to deliver high-value data solutions.
• Work closely with internal and external stakeholders to integrate new data sources and systems.
• Participate in Agile ceremonies, sprint planning, and technical design discussions.
• Contribute to architectural decisions and provide recommendations on emerging technologies and best practices.
• Support the delivery of AI and data-driven initiatives through the provision of scalable datasets and data services.

Security & Governance

• Implement data security controls including encryption, masking, access management, and auditing.
• Ensure compliance with enterprise data governance and security standards.
• Promote best practices around data protection, privacy, and regulatory compliance.

Required Experience

• Bachelor's Degree in Computer Science, Software Engineering, Data Engineering, Information Technology, or a related field.
• 3-5 years of experience in Data Engineering, Big Data Engineering, or related disciplines.
• Proven experience building and supporting enterprise-scale data platforms.
• Strong understanding of modern data architecture patterns and distributed systems.
• Experience delivering production-grade data solutions within Agile environments.

Preferred Certifications

• Databricks Certification
• Confluent Kafka Certification
• AWS Data Analytics Certification
• Microsoft Azure Data Engineer Associate
• Google Professional Data Engineer

Technical Skills

Big Data & Data Processing

• Apache Kafka
• Apache Spark
• Apache Flink
• Apache NiFi
• Apache Airflow
• Batch and Real-Time Data Processing

Data Architecture

• Data Modelling
• OLAP & Dimensional Modelling
• Change Data Capture (CDC)
• Data Warehousing
• Data Lake and Lakehouse Architectures

Programming & Development

• Python
• Scala
• Java
• Advanced SQL
• Git Version Control

Storage & Data Platforms

• PostgreSQL, Oracle, SQL Server
• NoSQL Technologies
• MinIO / S3 Object Storage
• Avro, Parquet, and ORC File Formats

Cloud & Infrastructure

• AWS, Azure, or Google Cloud Platform
• Docker
• Kubernetes
• Distributed Data Platforms

Desirable Skills

• Databricks and modern Lakehouse platforms.
• Delta Lake and Apache Iceberg.
• dbt and data transformation frameworks.
• Data Quality and Observability tooling.
• AI and Generative AI data preparation, including Retrieval-Augmented Generation (RAG).
• Enterprise analytics and reporting environments.
• Event-driven architecture and streaming platforms.
• Experience supporting machine learning and AI workloads.