Data Engineer (HealthTech)

About AssistRx

AssistRx 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.

Position Summary

As a Data Engineer, you’ll play a key role in shaping AssistRx’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.

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.

Requirements

• Bachelor’s degree in Computer Science, Math, Software Engineering, or a related field.
• 6+ years of experience in data engineering, data analytics, or software development.
• Advanced SQL skills with strong experience designing and optimizing queries for large datasets.
• Hands-on experience with ETL tools (e.g., Informatica, Talend, dbt, Azure Data Factory).
• Experience with healthcare data, including PHI/PII compliance requirements.
• Strong background in cloud-based data warehousing (Snowflake, BigQuery, etc.).
• Familiarity with open-source platforms and scripting languages (Python, Java, Linux, Apache).
• Working knowledge of BI and reporting tools (Power BI, Tableau, Cognos).
• Experience with big data technologies such as Spark, Hadoop, Hive, or MapReduce.
• Excellent communication, problem-solving, and collaboration skills with a proactive approach to

Benefits

• Supportive, progressive, fast-paced environment
• Competitive pay structure
• Matching 401(k) with immediate vesting
• Medical, dental, vision, life, & short-term disability insurance
• Opportunity to impact patient outcomes through data-driven healthcare technolo