Senior Data Engineer - Conversational AI (Remote)

Humana Remote
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November 23, 2022
San Antonio, Texas


The Senior Data Engineer designs, builds, and maintains data processing architectures and solutions enabling the efficient conversion of structured and unstructured data to insights at enterprise scale. The Senior Data Engineer work assignments involve moderately complex to complex issues where the analysis of situations or data requires an in-depth evaluation of variable factors.


The Senior Data Engineer Ingests data from internal and external sources utilizing cloud native platforms and software development best practices and patterns. Develops software tools that leverage artificial intelligence, machine learning, and big-data techniques to cleanse, organize, and transform data into insights and actions that enables Humana to better serve our members. Begins to influence department's strategy. Makes decisions on moderately complex to complex issues regarding technical approach for project components, and work is performed without direction. Exercises considerable latitude in determining objectives and approaches to assignments.

Responsibilities include:

  • Building systems around machine learning models
  • Building a cloud native platform to enable developers across the enterprise to integrate best in class conversational AI capabilities into their applications
  • Utilizing python, Kubernetes, Azure, Databricks, Azure Pipelines to build out the platform
  • Working alongside data scientists and product managers in agile teams
  • Develop Kubernetes ecosystem to build out service mesh and to build a framework to deploy real-time machine learning models
  • Build Python SDKs that be reused across teams for data acquisition and deployment


Required qualifications:

  • Bachelors degree or equivalent experience
  • 5 or more years experience as a developer, building systems and machine learning models
  • 2-3 years experience utilizing Python, Databricks and PySpark

Preferred qualifications:

  • Experience utilizing Kubernetes, Azure, Azure Pipelines highly preferred

Scheduled Weekly Hours


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