Data Engineer – Azure Databricks & Lakehouse (14‑Month)

Robotic Technologies Automation

Quincy (MA)

Presencial

USD 80 000 - 106 000

Tempo integral

há 3 horas
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Currículo e carta de apresentação personalizados, prontos a enviar.

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Resumo da oferta

Robotic Technologies Automation is seeking a Data Engineer in Quincy, MA to lead the design, development and optimization of large-scale data pipelines using Azure Databricks. The role focuses on Spark jobs, streaming, lakehouse architectures and performance tuning across Databricks environments.

The ideal candidate has hands-on experience with PySpark/Scala, SQL, and cluster configuration, with familiarity in DevOps pipelines, Azure services, and container orchestration (Docker/Kubernetes).

Qualificações

  • Develop and optimize Spark jobs, data transformations, and processing workflows.
  • Implement complex data streaming and transformation solutions using Azure Databricks.
  • Design and implement data warehouse/lakehouse solutions.
  • Monitor, debug, and resolve issues in live Databricks jobs.
  • Troubleshoot DevOps pipelines, Azure, and AKS services.
  • Build data ingestion, streaming, and transformation solutions.
  • Experience with Apache Big Data technologies and languages such as PySpark, R, or Java is advantageous.
  • Docker and Kubernetes experience is good to have.

Responsabilidades

  • Develop and optimize Spark jobs, data transformations, and processing workflows.
  • Implement Azure Databricks streaming and transformation solutions.
  • Design and implement data warehouse/lakehouse solutions.
  • Monitor and debug live Databricks jobs.

Descrição da oferta de emprego

Robotic Technologies Automation is seeking a Data Engineer in Quincy, MA to lead the design, development and optimization of large-scale data pipelines using Azure Databricks. The role focuses on Spark jobs, streaming, lakehouse architectures and performance tuning across Databricks environments.

The ideal candidate has hands-on experience with PySpark/Scala, SQL, and cluster configuration, with familiarity in DevOps pipelines, Azure services, and container orchestration (Docker/Kubernetes).

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