Data Engineer

Who we are

Founded in 1999, Quantum Health is a privately-owned, independent healthcare navigation organization. As the company that invented healthcare navigation, Quantum Health continues to set the standard and in 2025 acquired leading healthcare technology company Embold Health. This further strengthens the AI and provider search capabilities to guide members to the right care. Together, the teams lead the industry in healthcare navigation, simplifying care journeys, improving outcomes and controlling rising costs for organizations of all sizes. This role supports the Embold Health division.

We’re committed to building diverse and inclusive teams across our so if you’re excited about this position, we encourage you to apply – even if your experience doesn’t match every requirement.

 About the role

As a Data Engineer, you will serve as a key contributor in the ingestion, aggregation, structuring and analysis of terabytes of healthcare and operational data. You will build complex ETL and ELT systems that make consistent, reliable data available for both our data science and healthcare analysis teams, as well as our core products, which present this analytic data to both consumer and sophisticated business user audiences. Furthermore, you will take our data science team’s analyses and investigatory work and operationalize them into scalable, production-ready data pipelines and services that power analytics, reporting, and core product experiences.

 Location: This position is located at our Nashville, TN office with hybrid flexibility or may work remotely anywhere in the United States of America. 

 What you’ll do

• Design, build, and maintain scalable data pipelines that transform and deliver structured and unstructured data across the organization’s data ecosystem.
• Develop and operate complex ETL and ELT workflows using Azure Databricks, Apache Spark, and related data engineering technologies.
• Use Python, SQL, and other data engineering tools to efficiently transform, validate, and optimize data for analytical and operational use cases.
• Work with a variety of data storage and retrieval technologies, including Databricks, Elasticsearch, PostgreSQL, and other enterprise data stores.
• Collaborate closely with data architects, design teams, and cross-functional partners to define data solutions and support evolving data requirements.
• Support and operationalize analytics and data science use cases by delivering reliable, production-ready data assets.
• Foster a culture of teamwork, self-organization, and continuous improvement through innovative solutions.
• Assist team members in solving complex technical problems and improving the overall productivity and capabilities of the team.
• All other duties as assigned.

What you’ll bring

• Education: Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related field, or equivalent practical experience.
• 2+ years of experience in a data-focused technical role as a Data Engineer, ETL Developer, Data Analyst, or similar.
• Hands-on experience building and maintaining data pipelines and datasets in a Microsoft Azure environment.
• Strong working experience with Python and Apache Spark.
• Prior experience with Databricks.
• Solid understanding of relational databases, data modeling concepts, and data transformation best practices.
• Experience working with structured and semi-structured data formats such as JSON and XML, and consuming REST-based APIs.
• Demonstrated ability to analyze data, solve complex business problems, and improve data quality and reliability.
• Tremendous motivator, extraordinary interpersonal skills working with engineers.
• Commitment to data security, privacy, and ethical data handling practices.
• Trustworthy and accountable behavior, capable of viewing and maintaining confidential information daily. 

Preferred Qualifications

• Prior experience with Azure, including Databricks on Azure and Azure Synapse DW.
• Prior experience with Elasticsearch for search.
• Prior experience mentoring or guiding peers in areas of technical expertise.

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