Data Engineer

Wasl Group; Dubai; On-site; AED 150,000 - 200,000; Full time

Job summary

Wasl Group in Dubai is seeking an experienced Data Engineer to design, build, and optimize scalable data pipelines that support advanced analytics and BI across the organization.

This role requires a strong focus on data availability and quality, collaborating closely with data scientists and BI analysts, while utilizing cloud-native architectures, particularly on Azure. A bachelor’s degree and 5+ years of data engineering experience are essential.

Qualifications

• 5+ years of experience in data engineering.
• Proficiency in SQL and Python.
• Experience with cloud data platforms.

Responsibilities

• Design, develop, and maintain scalable batch and real‑time pipelines (ELT/ETL).
• Build and maintain data lakes, lakehouse layers, and curated datasets.
• Develop high‑performance SQL and Python code optimized for large datasets.
• Set up monitoring, alerting, and logging using observability tools.
• Contribute to data quality rules, governance, and metadata management.

Skills

SQL

Python

Big Data Technologies (Spark, Hadoop)

Data Orchestration

Data Warehousing (Fabric preferred)

Data Quality and Governance

Education

Bachelor’s degree in Computer Science, Engineering, or related field

Tools

Azure

Terraform

GitHub Actions

Azure DevOps

Job description

Job Title: Data Engineer

Reporting Line: Sr. Data Engineer

Division: Support Services - Business Excellence and IT

Department: Information Technology

The Data Engineer designs, builds, and optimizes scalable data pipelines and platforms that enable advanced analytics, BI, and AI use cases across the organization. This role ensures data availability, quality, lineage, and reliability, while leveraging modern cloud‑native architectures and engineering best practices. The Data Engineer collaborates closely with data scientists, BI analysts, and business teams to deliver secure, governed, and high‑performance data solutions.

Key Responsibilities and Performance Standards

• Design, develop, and maintain scalable batch and real‑time pipelines (ELT/ETL).
• Build and maintain data lakes, lakehouse layers, and curated datasets.
• Develop high‑performance SQL and Python code optimized for large datasets.

Data Reliability, Quality & Observability

• Set up monitoring, alerting, and logging using observability tools.
• Improve pipeline performance, optimize compute and storage costs, and ensure SLA adherence.
• Contribute to data quality rules, governance, and metadata management.
• Develop and deploy data solutions on cloud platforms (preferably Azure).
• Build infrastructure‑as‑code (Terraform, ARM, Bicep) for repeatable deployments.
• Implement CI/CD pipelines for data workflows (GitHub Actions, Azure DevOps).
• Partner with data scientists to prepare training datasets and MLOps pipelines.
• Work with BI teams to provide optimized semantic layers and analytical datasets.
• Participate in design reviews, architecture discussions, and sprint planning.

Documentation & Standards

• Maintain technical documentation, data dictionaries, lineage, and mappings.
• Contribute to engineering standards, best practices, and reusable templates.

Key Technical Skills and Proficiency Levels

• SQL and Relational Databases – Advanced
• Big Data Technologies (Spark, Hadoop) – Advanced
• Data Warehousing (Fabric preferred) – Intermediate
• Programming (Python, Scala) – Advanced
• Data Orchestration – Advanced
• Data Quality and Governance – Intermediate

Communications and Working Relationships

• Internal: Collaborates with Data Scientists, BI Analysts, and business stakeholders.
• External: May interact with technology vendors and service providers.

Selection Criteria – Essential

• Bachelor’s degree in Computer Science, Engineering, or related field
• 5+ years of experience in data engineering
• Proficiency in SQL and Python
• Experience with cloud data platforms

Desirable

• Master’s degree
• Experience with real‑time data processing
• Knowledge of data governance practices