Data Engineer

Qualifications

• Exceptional English communication skills, both written and verbal (C1 level Minimum).
• Enthusiastic, positive attitude, eager to work with others and solve problems.
• Strong experience designing and implementing enterprise data warehouses and modern data lake/lakehouse architectures (Databricks experience preferred).
• Proven experience building and maintaining production ELT and reverse ETL (rETL) pipelines.
• Experience working with HIPAA-compliant healthcare data and secure PHI management.
• Familiarity with Electronic Health Records (EHR) data and FHIR integrations is highly preferred.
• Strong understanding of modern data modeling, testing, and documentation best practices.
• Experience with analytics tools such as Hex is a plus.
• Comfortable leveraging AI tools to accelerate development while maintaining engineering quality.
• Self-starter with excellent analytical, problem-solving, and communication skills.
• Demonstrates ownership, accountability, precision, and the ability to thrive in a fast-paced startup environment.

Responsibilities

• Build and maintain scalable healthcare data infrastructure and pipelines.
• Develop and optimize enterprise data warehouse and lakehouse architecture.
• Design secure, HIPAA-compliant data models and PHI separation processes.
• Build and maintain ELT and reverse ETL workflows.
• Develop trusted datasets that support AI, analytics, and operational decision-making.
• Document, test, and improve data systems for long-term scalability.
• Collaborate with engineering and AI teams on data integration and platformdevelopment.
• Utilize AI tools to improve engineering productivity and workflow.
• Continuously monitor, improve, and optimize data quality and platform performance.
• Help establish best practices for data engineering across the organization.