Manager, Platform Operations

The Manager, Data Platform is a senior technical and strategic leader who owns the Azure data platform roadmap, leads the data engineering function, governs data modelling standards, and ensures the platform delivers scalable, reliable, high-quality, and governed data pipelines and storage environments that serve TAQA's analytical, AI, and operational reporting needs.

This role requires both deep Azure data engineering expertise and the strategic mindset to define platform direction, influence data investment decisions, and partner with the VP, Data Management and the Manager, Data and AI Governance to build a cohesive, governed, and high-performing data platform that positions TAQA Distribution at the forefront of data-led utility management in the UAE.

• Define and own TAQA Distribution's Azure data platform strategy and technical roadmap — evaluating emerging technologies (Microsoft Fabric, Delta Lake, Apache Iceberg, Databricks Lakehouse Platform), assessing their strategic relevance to TAQA's analytical and AI ambitions, and building a phased modernization roadmap that is aligned with the VP, Data Management's data strategy and TAQA's broader digital transformation agenda.
• Architect and govern TAQA's Azure Lakehouse platform — designing the multi-zone Medallion architecture (Bronze/Silver/Gold layers) on Azure Data Lake Storage Gen2 (ADLS), Azure Databricks, and Azure Synapse Analytics — ensuring the platform is structured for scalability, data quality progression, reusability, and governed analytical consumption across all data domains.
• Govern data platform architecture decisions — ensuring platform designs are scalable, cloud cost-optimized, secure, aligned with TAQA's enterprise architecture principles and data governance standards, and capable of evolving to support growing AI/ML, real-time analytics, and operational data integration workloads.
• Lead TAQA's data engineering function — directing the design, development, testing, and production operation of enterprise-scale ETL/ELT data pipelines using Azure Data Factory (ADF) for orchestration and Azure Databricks (PySpark, Spark SQL, Delta Live Tables) for distributed data processing — ingesting data from TAQA's operational systems including Oracle Fusion, Oracle CC&B, Maximo, HES/MDMS, SAP, and IoT/sensor data sources, into the Azure data platform accurately and reliably.
• Implement Data Ops engineering standards across the data platform team — including Infrastructure-as-Code (Terraform or Azure Bicep) for platform provisioning, CI/CD pipelines for data pipeline deployments via Azure Dev Ops, automated data quality testing frameworks (dbt tests, Great Expectations), and Git-based version control — ensuring data engineering delivery is reproducible, auditable, and operationally excellent.
• Govern data pipeline performance, reliability, and monitoring — implementing Azure Monitor, Databricks observability tooling, and ADF monitoring dashboards to ensure proactive detection and rapid resolution of pipeline failures, data quality exceptions, and performance degradation — maintaining high platform availability and data freshness SLAs for TAQA's analytical consumers.
• Define and enforce data modelling standards across TAQA's Azure data platform — governing dimensional modelling (star and snowflake schemas) for analytical workloads, Data Vault 2.0 structures for enterprise data warehouse flexibility and historical auditability, and semantic layer design using dbt, Azure Analysis Services, or Power BI datasets — ensuring data models are well-documented, performant, governed, and aligned with TAQA's key data domains (operational, customer, financial,…