Senior Data Engineer Healthcare Data Platforms

Job Title: Senior Data Engineer Healthcare Data Platforms

Experience: 8 12+ Years
Location: Hybrid / Remote
Job Overview

We are seeking a Senior Data Engineer with strong experience in healthcare data platforms and GCP cloud data engineering. The ideal candidate will design, develop, and support scalable healthcare data platforms and ETL/ELT pipelines using modern GCP data technologies.

The role requires hands-on experience with Dataproc, Data Composer, BigQuery, BigLake, Apache Iceberg, Starburst, dbt, and PySpark, along with healthcare data domains such as Claims, Member, Provider, or Clinical data.

Key Responsibilities

• Design, develop, and support scalable data pipelines and healthcare data platforms on GCP.
• Build and optimize ETL/ELT pipelines using PySpark, dbt, Dataproc, and Data Composer.
• Develop and maintain data solutions using BigQuery, BigLake, Apache Iceberg, and Starburst.
• Implement healthcare data integrations using APIs, SFTP, and Kafka.
• Design scalable data models and ensure data quality, reliability, and performance.
• Perform data validation, troubleshooting, and performance optimization across data platforms.
• Support production deployments, monitoring, troubleshooting, and issue resolution.
• Implement and maintain data governance, security, and data management best practices.
• Collaborate with architects, data analysts, business stakeholders, and engineering teams.
• Support healthcare data integration and data quality initiatives.
• Contribute to modern lakehouse architecture and large-scale distributed data processing.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, Data Engineering, Data Science, or a related field.
• 8+ years of experience in Data Engineering and Cloud Data Platforms.
• Strong hands-on experience with Google Cloud Platform (GCP).
• Experience building and supporting large-scale healthcare data platforms.

Mandatory Technical Skills

• GCP
• BigQuery
• BigLake
• Dataproc
• Data Composer
• Apache Iceberg
• Starburst
• dbt
• PySpark
• SQL
• ETL/ELT
• Kafka
• API Integrations
• SFTP
• Data Modeling
• Performance Optimization
• Production Monitoring & Troubleshooting

Mandatory Healthcare Domain Experience

Experience working with one or more healthcare data domains:

• Claims Data
• Member Data
• Provider Data
• Clinical Data

Candidates should also understand:

• Healthcare data integration
• Healthcare data quality
• Data governance
• Healthcare data management
• Data security practices

Preferred Qualifications

• Experience with healthcare interoperability standards such as FHIR, HL7, or EDI.
• GCP or other relevant cloud certifications.
• Experience with cloud-native data platforms.
• Experience working in Agile/Scrum delivery environments.
• Experience with modern lakehouse architectures and open table formats.
• Experience with cloud-native monitoring and observability.
• Experience implementing automated data quality practices.
• Experience optimizing large-scale distributed processing and analytical workloads.

Key Competencies

• Data Engineering & Architecture
• GCP Cloud Data Platforms
• Healthcare Data Engineering
• ETL/ELT Development
• Data Modeling
• Performance Optimization
• Data Quality & Governance
• Production Support & Troubleshooting
• Problem Solving & Analytical Skills
• Stakeholder Collaboration

Primary Skills

GCP, BigQuery, BigLake, Dataproc, Data Composer, Apache Iceberg, Starburst, dbt, PySpark, Kafka, APIs, SFTP, SQL, ETL/ELT, Data Modeling, Healthcare Data, Data Engineering

Good-to-Have Skills

FHIR, HL7, EDI, Healthcare Interoperability, Cloud Monitoring, Observability, Automated Data Quality, Lakehouse Architecture, Distributed Data Processing, GCP Certifications, Agile/Scrum