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Tier-1 brand, metro location, mid-level generalist role and broad tech requirements create high competition.
Core data engineering skills are transferable, though supply-chain domain knowledge adds moderate bias.
Explicit 4-7 years plus multiple required data engineering technologies increases filtering strictness.
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Owns the design, development, and maintenance of secure, performant data pipelines and architectures for structured and unstructured data within supply chain context.
Leads data engineering projects including coding, testing, debugging, and integration to improve data quality and integrity for machine learning and analytics.
Performs root cause analysis of data issues and implements automated corrective actions to enhance enterprise data accuracy and compliance.
Bachelor’s or Graduate degree in Computer Science, IT, Software Engineering, Statistics/Mathematics or related field or equivalent experience.
4-7 years work experience in data analytics, data engineering, data modeling or related domain; or 3-5 years with advanced degree.
Mandatory technical skills include SQL, Python, and experience implementing AI solutions for data quality problems.
Experience with AWS, Apache Hadoop, Kafka, Spark, ETL pipelines, data warehousing, and machine learning as relevant.
Experienced data engineer capable of leading projects and mentoring junior staff in large-scale data architecture environments.
Strong expertise in designing and maintaining data pipelines focused on improving data integrity and automating quality checks in a supply chain context.
Comfortable working cross-functionally to define and deliver actionable data products and possesses proficiency in multiple programming languages (Python, SQL, Scala, Java).