Senior Data Quality Engineer, Emirates Group

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Job Description

Emirates Group needs a Senior Data Quality Engineer who will join their Enterprise Data and Analytics team to develop and operate data quality assessment systems. The position focuses on ensuring reliable, scalable, and high-quality data pipelines that support Emirates Airlines and broader Emirates Group business operations through advanced testing, automation, and analytics support.

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Main Duties

  • Owners and analysts and architects and engineers create acceptance tests from their requirements. 
  • Strategies and plans which test system functionality and data quality and performance and security measures.
  • Automated testing systems which test data pipelines to confirm their operational dependability and performance. 
  • Datasets which they use to perform exploratory analysis and validation testing. 
  • Observability systems and data quality assessment tools throughout all data systems in the company. 
  • Technical problems while working independently to fix project problems. 
  • Analysis works through three tasks which include data profiling and data modeling and source-to-target mapping.
  • Data assets maintain metadata standards and data lineage tracking and governance standards for compliance.

Essential Qualifications

  • Educational background consists of a degree in either Computer Science Software Engineering or Computational Mathematics or a related field. 
  • Minimum of two years of data engineering experience which focuses on quality assurance and automation. 
  • Analytics platforms which include Data Lakes and Data Warehouses that utilize Big Data technologies. 
  • Expertise in automated testing which is applicable to complex enterprise data pipelines. 
  • CI/CD validation processes which are used to test ETL and ELT operations. 
  • Programming abilities through Python and Scala programming languages while also having proficiency in SQL. 
  • knowledge of data modeling and architectural principles as well as dimensional modeling techniques. 
  • demonstrates strong abilities in analytical work and collaboration while solving complex problems.

Technical Exposure

  • Big Data technologies include Spark and Hadoop which consists of HDFS, Hive, HBase, Oozie, Airflow and Apache NiFi. 
  • Microsoft Azure with its ADLS, Databricks, Azure Data Factory and Cloudera make up the cloud environment. 
  • The data platforms available include Snowflake and SQL and Data Vault 2.0 and Power BI and MicroStrategy. 
  • The integration and streaming technologies available include Kafka and SnapLogic and TIBCO and Spark Streaming. 
  • The CI/CD process requires users to work with Git and Jenkins and Azure DevOps and Kubernetes and Docker and SonarQube. 
  • Experience in programming languages include Python and Scala.