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Senior level and specialized Snowflake/Azure skills reduce applicants despite general Data Engineer demand.
Platform-specific Snowflake/Azure expertise and GDPR experience favor candidates from enterprise data backgrounds.
Explicit 10+ years plus specific Snowflake, Azure, and DataOps requirements make filtering strict.
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Own and evolve a modern enterprise data platform ensuring 99.9%+ reliability and high performance.
Architect and scale data solutions supporting analytics and data-driven products, including batch and real-time processing.
Lead and mentor engineering teams while collaborating with business and technology leaders to translate needs into scalable data solutions.
Bachelor’s degree in Computer Science, Information Systems, Data Engineering, Analytics, Statistics, or related field.
10+ years of data engineering experience including leadership responsibilities.
Expertise in Snowflake platform and Microsoft Fabric including Synapse, Data Factory Gen2, and Fabric Lakehouse/Warehouse.
Experience with data governance, data quality frameworks, and compliance such as GDPR.
Experienced leader capable of technical and team leadership for enterprise-scale data platforms in hybrid, multi-engine modern architectures.
Demonstrated ability to engage effectively with senior stakeholders to translate complex business needs into robust data solutions.
Comfortable operating in data-driven, multi-functional environments with strong focus on DataOps, DevOps, performance and cost optimization.