Azure Databricks Data Architecture Lead & ML

IRISSTAR Technologies; Abu Dhabi; Sur place; AED 300 000 - 600 000; Plein temps

Résumé du poste

IRISSTAR Technologies is seeking an senior data architect to lead architecture and design for data analytics initiatives in Abu Dhabi. You will architect scalable Lakehouse solutions using Azure Databricks and ADLS Gen2, and define data ingestion, transformation, and consumption frameworks.

The role requires 10-12 years of experience, strong governance and security capabilities, and leadership to mentor data engineering teams as you drive performance and cost optimization across the platform.

Qualifications

• 10-12 years of experience in data engineering, architecture or related roles.
• A proven track record leading data platforms on Azure, with Databricks expertise.
• Strong ability to design scalable Lakehouse architectures and govern data domains.

Responsabilités

• Lead architecture and design for data & analytics use cases.
• Design scalable Lakehouse architectures using Azure Databricks and ADLS Gen2.
• Define data ingestion, transformation, orchestration and consumption frameworks. Architect batch & real-time data processing solutions.
• Develop data models for Analytics, BI and AI/ML requirements.
• Establish data governance, security, monitoring and platform standards.
• Drive performance, cost optimization and scalability.
• Define CI/CD, DevOps and Infrastructure-as-Code standards.
• Provide technical leadership and mentor data engineering teams.
• Support technical roadmaps, solution design and effort estimation. Strong Azure Databricks & Data Architecture experience is essential.

Connaissances

Azure Databricks

Data architecture

Leadership / mentoring

Azure Data Platform

Outils

ADLS Gen2

Lakehouse architecture

Description du poste

IRISSTAR Technologies is seeking an senior data architect to lead architecture and design for data analytics initiatives in Abu Dhabi. You will architect scalable Lakehouse solutions using Azure Databricks and ADLS Gen2, and define data ingestion, transformation, and consumption frameworks.

The role requires 10-12 years of experience, strong governance and security capabilities, and leadership to mentor data engineering teams as you drive performance and cost optimization across the platform.