Lead Performance Engineer - Enterprise Data & Analytics

Job Purpose At Emirates Group our Analytics Centre of Excellence (ACoE) is a centralized unit that provides data and analytics support to Emirates Group businesses. TThis allows our businesses to make better decisions by using data and analytics to understand our customers, operations, and markets.The ACoE is an essential part of Emirates Group's digital transformation strategy. The unit is helping Emirates Group to become a more data-driven organization and to make better decisions by using data and analytics. As a Lead Performance Engineer, you will be working within the Enterprise Data & Analytics space, the Lead Performance Engineer is responsible for ensuring the performance, availability, scalability and reliability of a suite of products including big data technologies. The role will collaborate with multiple stakeholders to develop a fit for purpose performance engineering and testing strategy that covers all aspects of data products, including cross program dependencies. They will also drive a performance-driven culture and enables the engineering community to test earlier and test faster, thereby enabling faster time to market and built-in quality. In This Role You Will • Participate in all phases of the Performance Engineering lifecycle: Requirement Gathering, Design, Development, Scripting, Execution, Analysis, Troubleshooting, Tuning, Reporting. • Collaborate with Architecture, Solution Design and Development teams to design for Performance. • Ensure NFRs are defined for Features and Components, and ensuring every sprint team has a NFRs in their backlog. • Understand Non Functional Requirements effectively and build a Test strategy and Test translating into specific design and testing goals with required workload models. • Understand Big Data, Data Warehouse and BI applications, including the underlying architecture and technology stack, to recommend appropriate strategies and ensure the system performance is within defined SLAs. • Collaborate with feature teams to review and implement the performance improvement suggestions and tuning opportunities provided as part of the Performance Testing Analysis. • Work with observability teams to improve the visibility of Big Data and BI systems. • Evaluate testability of Features / Solutions. Work with architecture and design to build testability into the architecture. • Work with Site Reliability and Platform Engineers and Application teams to resolve, diagnose and identify bottlenecks. Qualification To be considered for the role, you must meet the below requirements: • Degree in a relevant field such as Computer Science, Computer Engineering or Software Engineering. • 5+ years’ experience in Performance Engineering, including testing, profiling and tuning, for highly available and scalable mission critical applications. • • 3+ years of experience in leading the performance engineering practice for a suite of products, including big data, data warehouse, BI and real time streaming applications. • Knowledge of data lake and date warehouse technologies with expertise in performance analysis and tuning data engines. • Expertise in working with large Cloud service platforms and solutions (e.g. Azure, Cloudera). • Expertise in reviewing architecture and design principles, and providing recommendations for improving application/system performance. Advanced knowledge of architecture and design concepts, including latest trends in technology • Proficient in detecting performance issues leveraging commercial and open source Load Testing tools, APM tools , Code Profilers and Observability frameworks. • Vast knowledge in building Workload models for complex systems using analytics and user-pattern analysis. • Expertise in building and tuning complex BI dashboards. • Proficient in at least one coding/scripting language. • Hands-on operational experience working with UNIX and Windows environments, and troubleshooting environment, OS or networks using packet sniffers and network monitoring tools. • Sound knowledge of commercial and open source log analytics tools. • Knowledge of Chaos engineering, Application Reliability and Disaster Recovery testing. • Knowledge of DevOps and how Continuous Performance Testing can be implemented using Load testing tools, APM tools, code profilers etc. Kdnowledge/skills • Experience working with stakeholders across IT and Business to analyse and interpret business requirements, and translate it to technical requirements. • Strong oral and written communication skills with demonstrable experience communicating with all technology partners, be it architecture, design, engineering, operations or infrastructure management. • Can collaborate with multiple teams / programs to deliver solutions interactively. • Excellent technical, interpersonal, analytical and problem-solving skills. • Ability to Multi-task, Prioritize and Manage time. • Ability to adapt and learn quickly in a complex and dynamic environment. • Self-starter and has passion for exploring and learning new technologies in Data analytics and Performance engineering space. Technology Domain Key Technologies/Tools • Performance Testing: Loadrunner Enterprise, Gatling Enterprise, Gatling OpenSource • Observability: Dynatrace, Prometheus, Grafana, Azure (Dashboards, Insights), OpenTelemetry, Oracle OEM • Big Data & distributed processing : Spark, Kafka, DataBricks, Azure Data Factory, Delta Lake, Elasticsearch, Iceberg, DuckDB, Fabric • AI Platforms: Claude Code, Azure AI Search, Fabric Agents, Databricks Genie, Dataiku • Data Analysis, Modelling and Reporting : Snowflake, Oracle, SQL, MicroStrategy, Power BI, Fabric Realtime • Cloud Technologies: Microsoft Azure • Integration and Messaging: Spark Streaming, Kafka, Solace, Eventhub • CI/CD: Git, Gitlab, Azure DevOps, Kubernetes, Docker, SonarQube Languages: Java, Python, Scala, Bash Find out what it’s like to live and work in our fast-paced, cosmopolitan home city in the Dubai Lifestyle section of our website www.emirates.com/careers Salary & benefits Join us in Dubai and enjoy an attractive tax-free salary and travel benefits that are exclusive to our industry, including discounts on flights and hotels stays around the world. 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Degree in Computer Science, Computer Engineering or Software Engineering. 5+ years’ experience in Performance Engineering, including testing, profiling and tuning for highly available and scalable mission critical applications. 3+ years of experience in leading the performance engineering practice for a suite of products, including big data, data warehouse, BI and real time streaming applications. Knowledge of data lake and data warehouse technologies with expertise in performance analysis and tuning data engines. Experience with large Cloud service platforms (e.g., Azure, Cloudera). Proficiency in detecting performance issues using Load Testing tools, APM tools, and code profilers. Experience building workload models for complex systems. Experience building and tuning complex BI dashboards. Proficient in at least one coding/scripting language. Hands-on experience with UNIX and Windows environments. Knowledge of log analytics tools, Chaos engineering, Application Reliability and Disaster Recovery testing. Knowledge of DevOps and Continuous Performance Testing using related tools.

Participate in all phases of the Performance Engineering lifecycle: Requirement Gathering, Design, Development, Scripting, Execution, Analysis, Troubleshooting, Tuning, Reporting. Collaborate with Architecture, Solution Design and Development teams to design for Performance. Ensure non-functional requirements (NFRs) are defined for features and components and that every sprint team has NFRs in their backlog. Translate Non-Functional Requirements into a test strategy and testing goals with required workload models. Understand Big Data, Data Warehouse and BI applications and their architectures to recommend strategies and ensure system performance meets defined SLAs. Collaborate with feature teams to review and implement performance improvements and tuning opportunities. Work with observability teams to improve visibility of Big Data and BI systems. Evaluate testability of features/solutions and work with architecture/design to build testability into the architecture. Collaborate with Site Reliability and Platform Engineers and Application teams to diagnose bottlenecks and resolve issues.