Job Description

Senior Data Engineer – Azure & Data Bricks

Mindtel Global

Job ID: 618783

06 Mar 2026

Job ID: 618783

06 Mar 2026

Job Location

United Arab Emirates

Experience

6 to 10 years

Qualification Level

Graduate; Post Graduate

Job Function

IT - Software

Skillset

Proficiency in Python, Data Bricks, SQL Server, and Azure Data Factory

Preferred Jobseekers

Jobseekers from any country

Key Responsibilities
Design and implement ETL pipelines using Data Bricks and Azure Data Factory
Manage, optimize, and maintain data storage solutions with SQL Server
Develop scalable data architectures and workflows to support analytics initiatives
Collaborate with cross-functional teams to gather and translate business data requirements
Apply DevOps practices to automate data operations and streamline deployments
Write, maintain, and optimize Python scripts for data processing and analysis
Monitor, troubleshoot, and enhance data pipelines for performance and accuracy
Stay updated with emerging data technologies, industry best practices, and cloud innovations

Requirements & Qualifications
Bachelor’s degree in Computer Science, Information Technology, or a related field
Minimum 6 years of experience in data engineering or similar roles
Strong hands-on expertise with Data Bricks, SQL Server, and Azure Data Factory
Proven experience in ETL pipeline development and optimization
Familiarity with DevOps practices and automation tools
Proficiency in Python for data processing, manipulation, and workflow automation
Strong analytical, problem-solving, and communication skills
Ability to work independently and take ownership of complex data initiatives

Preferred Qualifications:
Experience building enterprise-scale data solutions using modern Azure stack
Demonstrated ability to design clean, scalable, and efficient data architectures
Familiarity with advanced cloud-based analytics workflows and performance tuning

Salary, Benefits & Career Growth
Average Market Salary (Estimated):
AED 28,000 – AED 38,000 per month depending on experience and Azure data engineering expertise.

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