Senior Data Engineer

This employer will not sponsor applicants for employment visa status (e.g., H1-B) for this position. All applicants must be currently authorized to work in the United States on a full-time basis.

About Loopback

Loopback is a healthcare data company dedicated to improving access and outcomes for complex patients. We partner with health systems to grow and optimize specialty pharmacy performance, and we support life sciences organizations in accelerating evidence generation and expanding patient access through differentiated data and insights. Our work sits at the intersection of data, technology, and patient care, and we’re building a purpose-driven team that reflects that mission.

Founded in 2009, Loopback has been recognized by the Dallas Business Journal as one of the Best Places to Work, reflecting a culture grounded in collaboration, trust, and impact. Loopback has been recognized on the Inc. 5000 list of America’s fastest-growing private companies and consistently ranks among the fastest-growing companies in Dallas by the Dallas Business Journal.

Role Overview

Loopback Health is hiring a Senior Data Engineer to join our data engineering team. This is a hands-on role for someone who takes ownership of problems end-to-end; from identifying what needs to be built, to building it, to making sure it keeps running. The ideal candidate brings deep experience with healthcare clinical data, strong Databricks and cloud platform skills, and the kind of self-directed mindset where you don’t wait to be told what to do next. You will design, build, and maintain the data pipelines that power our analytics platform, ensuring the quality, availability, reliability, and security of critical clinical data. The Senior Data Engineer reports to the Senior Director of Engineering.

Key Responsibilities

• Design and build data pipelines for collecting, processing, and storing healthcare clinical data, and continuously improve them.


• Collaborate with data scientists, data integration specialists, analysts, and other stakeholders to understand data requirements and translate them into scalable solutions.


• Implement data validation, cleansing, and transformation processes to ensure data accuracy and consistency.


• Proactively monitor and troubleshoot pipeline performance, identifying and resolving issues before they become problems.


• Ensure data security and compliance with industry regulations, including HIPAA.


• Partner with the DevOps team to deploy and manage data pipeline infrastructure in our Azure cloud environment.


• Evaluate and adopt emerging tools, frameworks, and techniques that can improve our data platform: bring recommendations, not just questions.


• Leverage AI-assisted development tools and modern engineering workflows to accelerate delivery and improve code quality.

Qualifications

Technical Experience:

• 6+ years of hands-on data engineering experience, with significant exposure to healthcare clinical data.


• Proficient with Databricks for building and optimizing data pipelines.


• Strong programming skills in Python, Scala, or Java for data processing and automation.


• Experience with big data technologies such as Apache Spark, Hadoop, or Kafka.


• Working knowledge of cloud-based data platforms (Azure preferred; AWS or Google Cloud also valued) and related services.


• Strong SQL skills for data manipulation, querying, and performance optimization.


• Solid understanding of data modeling, ETL/ELT design principles, and data warehouse architecture.


• Demonstrated ability to troubleshoot complex data issues and deliver practical, well-documented solutions.


• Effective communication skills, you can explain technical decisions to both engineers and non-technical stakeholders.

Preferred Experience:

• Relevant certifications in data engineering, cloud platforms (e.g., Databricks, Azure), or healthcare data management.


• Understanding of machine learning concepts and their application to healthcare data.


• Familiarity with healthcare data standards (HL7, FHIR, EDI) and clinical data systems (Epic/Caboodle, Cerner, etc.).


• Experience with Snowflake or other modern cloud data warehouses.


• Comfort with AI-assisted development tools (e.g., GitHub Copilot, Claude Code, or similar).

Personal Characteristics:

• Agency and ownership: you identify what needs doing and drive it forward without waiting for permission or detailed instructions.


• A builder’s mindset: you’re always experimenting, prototyping, or exploring better ways to solve problems on your own initiative.


• Meticulous attention to detail, especially where data quality and accuracy directly impact healthcare outcomes.


• Strong problem-solving instincts and comfort navigating ambiguity in complex data environments.


• Collaborative and communicative: you work well across teams and contribute beyond your immediate scope.


• Genuine curiosity and a drive to keep learning, whether that’s new data technologies, healthcare domain knowledge, or AI tooling.


• Leadership presence: you mentor junior engineers, share knowledge proactively, and raise the bar for the team.


• Adaptability: you embrace change and are energized rather than frustrated by shifting priorities and new tools.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, or national origin.