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Popular Data Engineer title with specialized Databricks/Kafka skills and senior experience yields moderate competition.
Operational digital-twin and time-series expertise makes skills less transferable across industries.
Explicit 7+ years plus mandatory Databricks, PySpark, Kafka, Delta Live Tables and governance skills.
Design, develop, and maintain scalable data pipelines using Databricks, PySpark, Delta Lake, Kafka, and Terradata for digital twin platforms and operational analytics.
Implement and optimize real-time and batch data ingestion pipelines, ensuring data quality with Delta Live Tables and governance using Unity Catalog.
Collaborate with ML engineers and cross-functional teams to deliver feature-engineered datasets and support production data systems through monitoring and incident resolution.
7+ years of hands-on data engineering experience.
Proficiency with Databricks, PySpark, Delta Lake, Kafka, and Terradata data pipelines.
Experience with data quality tools such as Delta Live Tables expectations and data governance using Unity Catalog.
Work Experience Required: 7+ years as explicitly mentioned in Preferred Qualifications.
Experienced in building production-grade data pipelines, especially for real-time operational systems and digital twin platforms.
Skilled at working in agile, cross-functional, and distributed teams including ML and simulation engineers.
Domain exposure to industrial sectors like Manufacturing, Logistics, or Transportation and familiarity with operational state modeling and time-series data patterns.