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Data Engineer

Quest Analytics

Salary not specified
Oct 30, 2025
Overland Park, KS, US
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Quest Analytics is looking for a Data Engineer to build scalable infrastructure, implement automation, and enable cross-functional teams with reliable and accessible data to make healthcare more accessible.

Requirements

  • 3 years of work experience with ETL, data operations and troubleshooting, preferably in healthcare data.
  • Proficiency with Azure ecosystems, specifically in Azure Data Factory and ADLS.
  • Strong proficiency in Python for scripting, automation, and data processing.
  • Advanced SQL skills for query optimization and data manipulation.
  • Experience with distributed data pipeline tools like Apache Spark, Databricks, etc.
  • Working knowledge of database modeling (schema design, and data governance best practices.)
  • Working knowledge of libraries like Pandas, numpy, etc.

Responsibilities

  • Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
  • Review project objectives and determine the best technology for implementation. Implement best practice standards for development, build and deployment automation.
  • Run daily operations of the data infrastructure and support other engineers and analysts on data investigations and operations.
  • Monitor and report on all data pipeline tasks while working with appropriate teams to take corrective action quickly, in case of any issues.
  • Work with internal teams to understand current process and areas for efficiency gains
  • Write well-abstracted, reusable, and efficient code.
  • Participate in the training and/or mentoring programs as assigned or required.

Other

  • Adheres to the Quest Analytics Values and supports a positive company’s culture.
  • Responds to the needs and requests of clients and Quest Analytics management and staff in a professional and expedient manner.
  • Self-motivated and able to work in a fast paced, deadline-oriented environment
  • Excellent troubleshooting, listening, and problem-solving skills.
  • Proven ability to solve complex issues.