Data Engineer

Job description

Khazna was founded in 2012 and has grown rapidly into becoming the leading and trusted wholesale Data Center provider in the Middle East and North Africa region.

Through our Data Centers, we provide industry benchmark levels of power supply and cooling services to better serve the growing need for data center operations in the UAE and wider region.

We are seeking a
Data Engineer
to join our
Command & Control Center – Data Analytics & Reporting
team, reporting to the
Manager, Data & BI
.

This centralized role is responsible for designing, developing, and maintaining scalable data pipelines that support analytics, reporting, and AI/ML initiatives for data center operations.

The Data Engineer will ensure data integrity, optimize data architecture, and manage ETL (Extract, Transform, Load) processes across cloud and on-premises platforms to enable effective, data-driven decision-making.

Key Accountabilities:

• Support the development of scalable data warehouses, lakes and resilient data pipelines to support high-velocity data processing in a wholesale data center environment
• Design and implement Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) processes to clean, normalize and transform data from diverse sources, including Internet of Things (IoT) sensors, Building Management System (BMS) within data center operations
• Automate data ingestion, transformation and storage workflows for real-time analytics, ensuring low-latency insights for operational decision-making across data center environments
• Set up streaming data services to enable continuous migration of critical data center infrastructure metrics into analytics platforms for real-time monitoring
• Work with Integration teams, Data Warehouse engineers and Analytics teams to build highly optimized, resilient and scalable data center data processing architectures
• Define data sourcing strategies, tagging mechanisms and aggregation methods to ensure seamless availability of structured and unstructured data for data center analytics
• Collaborate with Data Scientists and Business Intelligence (BI) teams to enable AI/ML model development, predictive analytics and operational intelligence for data center operations
• Develop calculation methodologies for statistical computation of KPIs related to Power Usage Effectiveness (PUE), Water Usage Effectiveness (WUE), uptime and asset utilization in data centers
• Identify critical data points and sources that drive KPI computations and aggregate site-level metrics for centralized data center performance reporting
• Build reporting source files for dashboards, enabling executive leadership to monitor data center performance trends across regional and site-level operations
• Generate historical trend analyses, benchmarking individual data center site performance against portfolio-wide averages to drive efficiency improvements
• Conduct Exploratory Data Analysis (EDA) to identify patterns, anomalies and correlations that impact energy efficiency, workload distribution and infrastructure health in data centers
• Gather required historical and real-time data from internal platforms and external sources, ensuring comprehensive datasets for advanced analytics in data center environments
• Develop simulations and scenario models to analyse potential business impacts, optimize data center capacity planning and mitigate operational risks
• Update models and forecasting frameworks based on market trends, data center infrastructure expansion plans and internal priority shifts
• Research and implement cutting-edge data engineering techniques, contributing to industry-leading best practices in large-scale data center data infrastructure management
• Deliver data archiving, backup and disaster recovery strategies, ensuring high availability and business continuity for critical data center data assets
• Ensure seamless integration of data platforms with enterprise applications, enabling end-to-end visibility and automated decision-making across the data center ecosystem

Minimum Qualifications:

• Bachelor's or master's degree in computer science (or) related to Data Engineering
• Certifications in cloud data platforms preferred
• 4+ years of experience in data engineering, ETL development or database management
• Strong proficiency in SQL, Python or Scala
• Experience with cloud data platforms (AWS, Azure, GCP)
• Hands-on experience with data pipeline tools like Apache Airflow, Kafka or Spark
• Understanding of data modeling, warehousing and governance principles

Additional skills:

• Ability to troubleshoot complex data challenges, optimize pipeline performance and drive continuous improvements in large-scale infrastructure
• Strong ability to work across Data Science, Engineering, IT and Business Intelligence teams to align data solutions with business needs
• Expertise in translating technical data models and engineering concepts into clear insights for non-technical stakeholders

Training/Certifications Preferred:

• AWS Certified Data Analytics – Specialty
• Google Professional Data Engineer
• Microsoft Certified: Azure Data Engineer Associate
• Apache Spark Developer Certification

Required Skill Profession

Other General