We are looking for a lead Azure data quality engineer to join our team. The ideal candidate will have a proven track record in leading and delivering Azure Data Analytics solutions with Enterprise level organizations. You will be able to create and deliver a BI vision with customers across many sectors. You will be highly proficient working with business stakeholders and directing project teams and will have direct experience of a range of BI Tools and Platforms.
Key Deliverables:
• The role involves leading and championing quality practices along with designing and implementing data quality and automation platforms.
• They will also provide support and maintenance to technical analytics solutions and products that support group businesses.
• Support in building the technical design by contributing in the analysis of data application and ensuring quality related features are build into the solution.
• Work on and guide engineers on problems of diverse scope where analysis of data requires evaluation of identifiable factors and select methods to validate and automate the solution.
• Drive & mentor creation of test strategies and test plans validating the core business problem and translating them into tests around code functionality, data quality, performance, and security.
• Build platforms for automated tests / jobs of moderate to high scope and complexity across all stages of the data pipeline. Conduct code reviews to check for good coding & design practices and adherence to published coding standards and guidelines.
• Build and enhance data quality rules and platforms for observability across the data pipeline.
• Perform and support team debugging complex issues, resolve blockers.
Mandatory Skills:
• Data Engineering experience with focus on quality & automation
• Experience 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
• Seasoned in building data quality platforms for highly complex data architectures performing automated checks running in a CI and in production for data observability
• Experienced in leading team to build enablers / practices to identify quality issues across complex data pipelines running on big data technologies and defining rules for validating health of the data
• Proficient in at least 1 language (Scala / Python) for building ETL jobs in a distributed computing environment
• Strong SQL querying skills is required
• Experienced in a wide variety of testing methods and tools covering functional, performance, security tests across individual jobs, pipelines and end to end across enterprise.
• Good understanding of data architecture concepts such as data modelling, Big Data storage, and dimensional modelling
• Good experience of working with jobs in data pipelines and define metrics / measures to ensure correctness of the data
• Experience with batch and real-time data ingesti tools and technologies handling massive quantities of data (structured and unstructured)
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