Senior Data Engineer Healthcare Data Platforms
Job Description
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