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Mid-tier employer, popular data-engineer skills but senior 10-year requirement and non-metro reduces applicant density.
Requires domain-specific Azure and data architecture experience but skills remain moderately transferable across industries.
Explicit 10-year requirement plus multiple mandatory Azure/Databricks and data-architecture skills enforces strict filtering.
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Design, develop, test, and deploy data integration processes using tools like Azure Data Factory, Databricks, and Microsoft SSIS.
Lead and coach multiple team members on data integration projects, ensuring quality documentation and adherence to best practices.
Architect and set direction for enterprise self-service analytics and BI reporting solutions using tools such as Power BI, Tableau, and SQL Server Reporting Services.
10 years industry experience in data integration with tools like Databricks, Azure Data Factory, etc.
Minimum 5 years experience in data architecture or data modelling.
Bachelor’s degree in Computer Science, Data Science, or related field (Master’s preferred).
Strong experience with big data frameworks (Spark, Hadoop, Hive), data modelling tools, multiple database platforms, Agile processes, and CI/CD tooling.
Experienced in designing and managing end-to-end data pipelines and architectures in cloud environments, particularly Azure.
Skilled in data warehousing, OLTP systems, and modern data architecture philosophies (Dimensional, ODS, Data Vault).
Capable of collaborating cross-functionally with data scientists, analysts, and technical teams to deliver scalable BI and analytic solutions.