Senior Data Engineer

Job Title: Senior Data Engineer – Google Cloud Platform (GCP) Location: Remote, USA Experience Level: 8–10 years Employment Type: Full-Time (W2 or 1099) Compensation: Up to $120,000 per year + Benefits (based on experience) About the Role We are seeking an experienced Senior Data Engineer (GCP) with strong expertise in healthcare data systems to join our growing data engineering team. The ideal candidate will have a deep understanding of HIPAA-compliant architectures, FHIR/HL7 data standards, and GCP cloud-native data platforms. You’ll be responsible for building secure, scalable, and compliant data pipelines that power clinical analytics, population health, and healthcare operations. Key Responsibilities • Design, build, and maintain HIPAA-compliant ETL/ELT data pipelines using Dataflow, Dataproc, or Apache Beam. • Develop robust and optimized data warehouses and marts using BigQuery and Cloud Storage. • Work with healthcare-specific data formats — HL7, FHIR, CCD, and EDI X12. • Integrate clinical, claims, and operational data from multiple sources (EHR, EMR, payer systems). • Build and manage data workflows using Cloud Composer (Airflow) for orchestration. • Collaborate with data analysts and data scientists to provide curated datasets for analytics and ML. • Implement data quality, metadata management, and data governance frameworks. • Ensure compliance with HIPAA and HITRUST standards in all data operations. • Support DevOps processes, CI/CD pipelines, and infrastructure as code (Terraform, Cloud Build). • Work in an Agile/Scrum environment and contribute to architecture reviews and technical designs. Required Skills & Experience • 8–10 years in data engineering, with at least 4+ years on GCP (BigQuery, Dataflow, Dataproc, Pub/Sub, Composer). • Proven experience working with healthcare datasets (EHR, EMR, claims, payer, or clinical data). • Strong expertise in Python (PySpark) and Advanced SQL for data transformations. • Knowledge of FHIR/HL7 standards and healthcare data integration practices. • Experience with data modeling, data lakes, and data warehouse architectures. • Familiarity with data privacy laws and compliance frameworks (HIPAA, HITRUST). • Strong knowledge of Terraform, Docker, and CI/CD tools for deploying data solutions. • Proficiency with version control systems (Git) and Agile development tools (JIRA, Confluence). Preferred Qualifications • GCP Professional Data Engineer Certification. • Experience in ML pipelines or integrating AI/ML models for clinical predictions. • Knowledge of FHIR API integration and Google Cloud Healthcare API. • Experience with Looker or Power BI for healthcare analytics reporting. • Familiarity with AWS HealthLake or Azure Health Data Services (for cross-cloud interoperability). Soft Skills • Excellent communication and collaboration with clinical, technical, and compliance teams. • Strong analytical mindset and attention to data accuracy. • Ability to work autonomously in a fully remote U.S. team. • Leadership in mentoring junior engineers and defining cloud data standards. Tech Stack Languages: Python, SQL, PySpark GCP Tools: BigQuery, Dataflow, Pub/Sub, Dataproc, Composer, Healthcare API Orchestration: Cloud Composer (Airflow) Infra & CI/CD: Terraform, Git, Jenkins, Cloud Build Data Formats: FHIR, HL7, CCD, JSON, CSV, Parquet