indeed
Senior Data Quality Engineer
The Emirates Group
Dubai, UAE
Senior
Onsite
Discovered 3 weeks ago
Data QualityData AutomationData AnalysisData ModellingData GovernanceData Pipeline
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Data QualityData AutomationData Analysis
Role Overview
We are looking for a Senior Data Quality & Automation Engineer to work on technology development and problem resolution in the Enterprise Data & Analytics space. The role involves designing and implementing data quality and automation platforms, and providing support to technical analytics solutions
Key Skills for This Role
Data QualityData AutomationData AnalysisData ModellingData GovernanceData Pipeline
Full Job Posting
Job Overview
We are looking for a Senior Data Quality & Automation Engineer to work on technology development and problem resolution in the Enterprise Data & Analytics space. The role involves designing and implementing data quality and automation platforms, and providing support to technical analytics solutions
Qualifications & Experience
- Degree in a relevant field such as Computer Science, Computational Mathematics, Computer Engineering, or Software Engineering.
- Specialization or electives in a Data & Analytics field (e.g. Data Warehousing, Data Science, Business Intelligence).
- Minimum 2+ years of Data Engineering experience with a focus on quality & automation.
- Minimum 2+ years of testing, automation, and support experience in analytics applications such as Data Lake and Data Warehouse (preferably using the Big Data stack and Microsoft Azure cloud infrastructure).
- Experience with batch and real-time data ingestion/integration tools and technologies handling massive quantities of data (structured and unstructured).
- Exposure to data architecture concepts such as data modelling, Big Data storage, and dimensional modelling.
- Experience with jobs in data pipelines and defining metrics/measures to ensure correctness of the data.
- Programming (Python or Scala) and SQL querying skills.
In this role you will
- Work closely with product owners, analysts, software engineers, and architects to understand the technical landscape and context of deliveries to refine complex functional and non-functional requirements and translate them into fit-for-purpose acceptance tests.
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