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Specialized Azure/Databricks senior role with narrower applicant pool and modest employer brand reduces competition.
Core Azure Databricks data engineering skills transfer widely, though semiconductor domain knowledge adds moderate bias.
Explicit 10-13 years, mandatory Azure/Databricks skills and leadership make shortlisting highly selective.
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Design and evolve scalable, secure data solutions for enterprise reporting, advanced analytics, and AI workloads.
Lead and mentor the data engineering team, driving best practices and delivery excellence.
Collaborate with cross-functional teams to translate business requirements into high-impact data platforms using Azure and Databricks technologies.
Bachelor’s degree in technology or engineering required.
10-13 years in Data & Analytics with 5+ years hands-on experience in Azure data engineering technologies.
3+ years in technical lead or data engineering leadership roles.
Mandatory hands-on skills in Azure Data Factory, Databricks, PySpark, SQL, and understanding of Databricks Unity Catalog and CI/CD with DevOps.
Experienced leader capable of managing and mentoring data engineering teams in a technical capacity.
Proven ability to design AI-ready, scalable, and secure data platforms in complex enterprise environments.
Strong collaborator able to partner with business, architecture, data science, and product teams to deliver data solutions aligned with business outcomes.