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Metro location, recognizable global brand, and popular Data Engineer title increase candidate competition.
Core data engineering skills transfer across industries, though retail and supply-chain domain experience is preferred.
Explicit 12+ years, leadership expectations, and specific streaming/cloud/data stack make shortlisting highly strict.
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Lead delivery of an individual data engineering track within the Supply Chain & Planning Data Domain, handling requirements analysis, development, testing, deployment, and production support.
Architect and develop scalable batch and event-driven real-time data pipelines and data products using tools like Kafka, Google Pub/Sub, Spark Streaming, and cloud data platforms.
Provide technical leadership, ensure data quality/governance, troubleshoot issues, and collaborate globally to deliver reliable, high-value data solutions.
12+ years of experience in Data Engineering, Data Warehousing, or related roles with large-scale data solution delivery.
Proficiency in SQL and Python; experience with big data technologies like Spark, Flink, Hive; and event-driven streaming platforms such as Kafka or Google Pub/Sub.
Experience with cloud platforms (preferably Google Cloud Platform) and data transformation frameworks like dbt, PySpark, or Dataflow.
Flexible to overlap with U.S. time zones for global collaboration. B.E. in Computer Science is a plus but not mandatory.
Experienced technical leader capable of independently driving a critical data engineering track, including end-to-end delivery and stakeholder engagement.
Deep expertise in event-driven architectures and real-time streaming data pipelines within a supply chain or retail domain context.
Comfortable working in a globally distributed team environment requiring coordination across geographies and time zones.