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Mid-level, popular Data Engineer role with broad Azure/ETL skills increases applicant competition.
Data engineering skills are transferable, but Azure/SQL Server focus requires some platform-specific experience.
Multiple explicit years and required Azure, SQL Server, and CI/CD skills enforce strict filters.
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Own the design and build of automated processes to measure data quality, data transmission failures, and data load errors during a client's EDW migration from on-prem SQL Server 2016 to Azure Cloud.
Collaborate with data engineers, business analysts, and report developers to define data quality requirements and create dashboards/reports showcasing data quality metrics.
Analyze and improve existing systems and data pipelines, including data profiling, data modeling (Kimball dimensional modeling), and optimizing CI/CD processes using Azure DevOps.
Bachelor's Degree or higher in Engineering, Computer Science, or a related technical field.
Minimum 5+ years of experience designing, building, and supporting data pipelines, including at least 2+ years creating automated data quality measurement solutions for ETL processes.
At least 1+ year recent experience with Azure Data Services (Azure Data Catalog, Blob Storage, Data Lake Storage, Synapse Analytics, Analysis Services, Data Factory).
Strong experience with Microsoft SQL Server (preferably 2016), understanding of Power BI and DAX, ability to read/edit PowerShell scripts, and experience with CI/CD using Azure DevOps.
Experienced data engineer skilled in automating data quality controls and measurement within complex cloud migration projects.
Familiar with Azure Data services ecosystem and Microsoft SQL Server, able to integrate data quality processes within advanced ETL and CI/CD frameworks.
Capable of cross-functional collaboration, translating business data quality needs into technical specifications and supporting report developers and senior engineers.