Senior Google Cloud Platform Data Engineer

Job Title: Senior Google Cloud Platform Data Engineer

Job Location: Nashville, TN

Job Type: Contract

Pay Range: $50.00hr - $55.00hr

Job Overview:

As a Consulting Data Engineer, the successful candidate will architect, build, and optimize the next generation of real-time healthcare data platforms and event-driven architectures. The candidate will play a foundational role in moving clinical, operational, and financial data away from legacy batch processing toward high-throughput, near-zero-latency streaming pipelines. In this role, the candidate will champion modern data engineering practices, design highly scalable cloud-native pipelines, and mentor a growing team of engineers. The candidate will bridge the gap between complex electronic health records (EHR) and data consumers enabling data scientists, software engineers, and clinical analysts to securely access, stream, and query compliant data at scale to improve patient outcomes and operational efficiency.

Core Responsibilities:

• Architect Real-Time Pipelines: Design, implement, and monitor high-throughput, fault-tolerant streaming pipelines that ingest and process millions of concurrent healthcare data events (e.g., live telemetry, HL7 feeds, ADT messages).
• Scale Google Cloud Infrastructure: Build and maintain scalable, secure, and cost-effective cloud data infrastructure using Google Cloud healthcare-native tools and Infrastructure as Code (IaC).
• Enforce Healthcare Compliance & Security: Uphold strict data security protocols (HIPAA, HITRUST, SOC2) by building robust data lakehouse architectures that enforce PHI/PII masking, role-based access control (RBAC), and encryption at rest and in transit.
• Enable Self-Service Data & Interoperability: Build out streaming data ecosystems that support modern healthcare interoperability, managing real-time data catalogs and schema registries.
• Promote Code Excellence: Write modular, highly reusable, and performance-tested code; lead code reviews and establish standardized CI/CD automated deployment workflows.
• Optimize Data Reliability: Set and champion strict SLAs for clinical data delivery, establish automated data-quality testing, and implement proactive system monitoring and alerting.
• Collaborate & Mentor: Work closely with Data Architects, Clinical Product Managers, and AI/ML teams to translate healthcare requirements into technical blueprints while mentoring mid-level engineers.

Required Qualifications:

• 13+ years of experience in dedicated data engineering, data architecture, or distributed systems software engineering roles.
• 4+ years of experience specifically within the healthcare domain (payer, provider, digital health, or health tech).
• Google Cloud Certified Professional Data Engineer (or equivalent proven expert-level architecture experience on Google Cloud Platform).
• Advanced Event-Driven Architecture: Mastery of high-volume streaming technologies including Apache Kafka and Google Cloud Pub/Sub for decoupled, real-time message routing.
• Stream Processing: Deep hands-on experience with Apache Flink or Google Cloud Dataflow (Apache Beam) for real-time streaming, complex event processing (CEP), windowing, and streaming data transformations.
• Interoperability Standards: Deep expertise working with FHIR (Fast Healthcare Interoperability Resources) JSON structures, HL7 v2/v3 messaging, and DICOM imaging standard streams.
• Google Cloud Platform Healthcare Tools: Hands-on experience implementing and scaling the Google Cloud Healthcare API (specifically FHIR stores and HL7v2 stores).
• EHR Integration: Experience integrating streaming pipelines with major EHR systems (such as Epic, Cerner, or Meditech).
• Google Cloud Ecosystem: Technical mastery of BigQuery (including partitioning, clustering, and streaming inserts), Cloud Storage, Dataproc, and Cloud Composer (Apache Airflow).
• Programming Languages: Proficiency in Python, Scala, or Java, with a strong focus on writing optimized code for distributed computing platforms (like Spark or Beam).
• Modern Data Stack & Modeling: Mastery of modern analytics engineering frameworks (such as dbt), dimensional data modeling, and lakehouse architectures (e.g., Iceberg, Delta Lake).
• DevOps & Automation: Robust experience building automated CI/CD pipelines (GitHub Actions, GitLab CI) and managing infrastructure using Terraform.

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• Medical, Dental, and Vision Insurance
• 401(k) Retirement Plan
• Health Savings Account (HSA)
• Disability Insurance (Short-Term and Long-Term)
• Life and AD&D Insurance
• Paid Sick Leave (where required by applicable state or local law)
• Supplemental Insurance Plans
• Identity Theft Protection
• Pet Insurance
• Employee Wellness Programs
• Employee Assistance Program (EAP)
• Career Growth and Professional Development Opportunities