Principal Data Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Establish and uphold data engineering methodologies, pipeline standards, and architectural guidelines.

• Spearhead the design of scalable frameworks for data processing and transformation models related to claims, encounters, risk adjustment, and member data.

• Ensure accountability for the reliability of the platform and the quality of data outcomes.

• Utilize machine learning and automation techniques in operational data engineering environments.

• Develop and consistently enhance high-performance cloud-based data pipelines for both real-time and batch processing workflows.

• Act as the technical subject matter expert in data engineering.

• Guide engineers through architecture evaluations, design discussions, and internal documentation.

• Assess emerging data technologies and provide recommendations on build-versus-buy decisions.

• Contribute to the multi-year roadmap for data platform engineering.

• Leverage expertise in Medicare Advantage, CMS, HIPAA, HEDIS, and risk adjustment to deliver compliant, audit-ready healthcare data solutions.

• Offer informal technical leadership and subject matter expertise to Data Engineers and Senior Data Engineers.

• Carry out essential physical functions, including talking, hearing, standing, walking, sitting, handling objects or controls, reaching, and occasionally lifting up to 10 pounds.

⛳️ Requirements

• Over 10 years of progressive experience in data engineering, demonstrating platform engineering at scale.

• At least 5 years of experience in the healthcare sector, health insurance, or a Medicare Advantage environment.

• Proven experience in building and governing enterprise data platforms utilizing Apache Kafka, Databricks, and non-relational databases.

• Proficient in designing intricate ETL/ELT pipelines in cloud environments (Azure, AWS, or GCP).

• Familiarity with HIPAA-compliant data environments handling PHI/PII datasets.

• Experience in setting engineering standards or architectural frameworks adopted by others.

• Previous role as a technical lead in a data platform modernization or cloud migration project.

• Exposure to AI tools and their application within the data platform domain.

• Bachelor's degree in Computer Science, Information Systems, Data Science, Engineering, or a related technical field; an equivalent combination of education and experience is acceptable.

• Demonstrated proficiency with cloud data platform tools such as Azure Databricks or Azure Data Factory, or equivalent; hands-on experience can substitute for formal certification.

• Expertise in Kafka, Databricks, Apache Spark, and cloud-native tools.

• Extensive experience with Azure, AWS, or GCP data services, data lakes, lakehouses, and streaming architectures.

• Ability to operationalize machine learning and automation within production data engineering pipelines, including feature stores and model serving infrastructure.

• Advanced understanding of HIPAA, HL7/FHIR, ICD-10/CPT codes, CMS data submission standards, and governance of PHI/PII data.

• Capability to design scalable relational and non-relational data models.

• Advanced SQL skills and production-level experience in Python, Scala, or Java.

• Experience in implementing data quality frameworks, lineage tracking, and metadata management.

• No licensure required.

🏝️ Benefits

• Fully remote work.

• Opportunities for growth and innovation.

• Equal employment opportunity.