Senior Data Engineer

About This Role

This Senior Data Engineer role involves designing, building, and maintaining robust data pipelines for healthcare clinical data, ensuring data quality, reliability, and security for Loopback Health's analytics platform. The position requires end-to-end ownership, collaboration with various stakeholders, and continuous improvement of data processes within an Azure cloud environment.

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

Requirements

• 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

Qualifications

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

Nice to Have

• 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)

Skills

* Required skills