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Databricks DevOps - Remote

Roles & Responsibilities

  • Experience handling data engineering projects involving batch and streaming ingestion.
  • Proficiency in SQL development, data modeling, and managing both structured and unstructured data.
  • Expertise in PySpark and Python; hands-on experience with Azure Data Factory, Azure Databricks, and Azure Storage.
  • Proficient in CI/CD and DevOps practices, productionizing data pipelines, and testing automation (e.g., Pytest).

Requirements:

  • Oversee and manage data engineering projects for batch and streaming ingestion.
  • Develop, model, and manage SQL databases.
  • Implement and maintain data pipelines using Azure tools and Python.
  • Establish and maintain CI/CD pipelines and DevOps practices for production-grade data solutions, including automated testing.

Job description


Position: Databricks Devops Engineer
Location: Remote
Duration: long term
Rate: DOE

U.S. Citizens and those who are authorized to work independently in the United States are encouraged to apply. We are unable to sponsor at this time

Requirements:
  • Experience handling data engineering projects involving batch and streaming ingestion.
  • Proficiency in managing both structured and unstructured data.
  • Strong background in SQL development and data modeling.
  • Expertise in PySpark and Python.
  • Knowledge and experience with Azure Data Factory, Azure Databricks, and Azure Storage.
  • Familiarity with healthcare data and the healthcare domain.
  • Proficient in CI/CD, DevOps practices, and productionizing data pipelines.
  • Experience with testing automation, ideally using Pytest or similar frameworks.

Responsibilities:
  • Oversee and manage data engineering projects for both batch and streaming ingestion.
  • Develop, model, and manage SQL databases.
  • Implement and maintain data pipelines using Azure tools and Python.
  • Ensure data solutions align with healthcare standards and requirements.
  • Establish and maintain CI/CD pipelines and DevOps practices for production-grade solutions.
  • Automate testing processes within data pipelines.

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