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Data Engineer; HealthTech

Job in Riverside, Riverside County, California, 92504, USA
Listing for: AssistRx
Full Time position
Listed on 2026-01-12
Job specializations:
  • IT/Tech
    Data Engineer, Data Analyst, Data Security, Data Warehousing
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Position: Data Engineer (HealthTech)

Data Engineer Position

Assist Rx transforms the patient journey through technology, helping patients access life-saving therapies faster and more efficiently. Our platform connects the healthcare ecosystem patients, providers, payers, and manufacturers through data-driven solutions that improve care delivery and outcomes.

If you're passionate about data, innovation, and healthcare technology that truly makes a difference, we'd love for you to join our team.

As a Data Engineer, you'll play a key role in shaping Assist Rx's data ecosystem designing, building, and optimizing data pipelines that drive insights, enable automation, and power smarter decisions across the business. You'll own data architecture best practices, oversee ETL design and performance, and ensure seamless data flow across our systems including Azure, dbt, Snowflake, and Salesforce environments.

This is a hands-on, high-impact role for someone who thrives on solving complex data challenges, collaborating cross-functionally, and building scalable systems that support both internal and client-facing solutions.

Key Responsibilities:

  • Design and implement robust ETL pipelines using Azure Data Factory, dbt, Snowflake, and Salesforce for client data migrations and integrations.
  • Build processes for data cleansing, validation, and transformation to ensure high data quality before migration and reporting.
  • Create and maintain detailed data flow documentation for all client implementations and internal processes.
  • Partner with internal stakeholders to support the architecture and scalability of Salesforce multi-tenant solutions and downstream data products.
  • Continuously evaluate and implement new data integration tools and technologies, training peers on best practices.
  • Identify opportunities to improve efficiency, automation, and data consistency across shared data processes.
  • Contribute to the development of enterprise data lakes, data vaults, and MDM solutions that support business intelligence and analytics.
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