Experience: 8 12+ Years
Location: Hybrid / Remote
Job Overview We are seeking a Senior Data Engineer with strong experience in healthcare data platforms and Google Cloud Platform cloud data engineering. The ideal candidate will design, develop, and support scalable healthcare data platforms and ETL/ELT pipelines using modern Google Cloud Platform 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 Google Cloud Platform.
- 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 (Google Cloud Platform).
- Experience building and supporting large-scale healthcare data platforms.
Mandatory Technical Skills
- Google Cloud Platform
- 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.
- Google Cloud Platform 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
- Google Cloud Platform 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
Google Cloud Platform, 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, Google Cloud Platform Certifications, Agile/Scrum
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