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Remote role with reputable brand but senior, specialized data engineering reduces applicant density.
Core data engineering skills are transferable, though supply-chain domain knowledge moderately preferred.
No explicit years or mandatory tech listed, but senior enterprise data and customer-facing experience expected.
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Design, build, and scale data solutions in partnership with enterprise customers to support business-critical applications and analytics.
Operate at the intersection of Data Engineering, Product, Engineering, and Customer Success teams for end-to-end delivery of data platforms.
Drive outcomes that enable AI-powered monitoring and predictive analytics to improve supply chain resilience and risk management.
Experience: Senior-level Data Engineer with proven expertise in modern data platforms (specific years not explicitly mentioned).
Must have strong customer engagement skills to partner directly with enterprise customers.
Work Experience Required: Not explicitly mentioned in the JD.
Notice Period: Not explicitly mentioned in the JD.
Experienced in handling data engineering roles that require close collaboration with cross-functional teams including Product and Customer Success.
Comfortable working fully remote with responsibility for high-impact, business-critical data solutions.
Skilled at aligning data platform development with predictive analytics and AI-driven supply chain risk management objectives.