Senior GCP Data Engineer

Cynet Systems • Nashville, TN

1d

About The Position

As a Consulting Data Engineer, the successful candidate will architect, build, and optimize next-generation real-time healthcare data platforms and event-driven architectures. The role is foundational to moving clinical, operational, and financial data away from legacy batch processing toward high-throughput, near-zero-latency streaming pipelines. The engineer will champion modern data engineering practices, design scalable cloud-native pipelines, and mentor a growing team.

The position bridges 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.

Requirements

• 13 or more years of experience in dedicated data engineering, data architecture, or distributed systems software engineering roles.
• At least 4 years of experience in the healthcare domain, such as payer, provider, digital health, or health tech.
• Google Cloud Certified Professional Data Engineer certification or equivalent proven expert-level architecture experience on GCP.
• Mastery of high-volume streaming technologies, including Apache Kafka and Google Cloud Pub/Sub.
• Deep hands-on experience with Apache Flink or Google Cloud Dataflow (Apache Beam) for real-time streaming, complex event processing, windowing, and streaming data transformations.
• Deep expertise with FHIR JSON structures, HL7 v2/v3 messaging, and DICOM imaging standard streams.
• Hands-on experience implementing and scaling the Google Cloud Healthcare API, specifically FHIR stores and HL7v2 stores.
• Experience integrating streaming pipelines with major EHR systems such as Epic, Cerner, or Meditech.
• Technical mastery of BigQuery, including partitioning, clustering, and streaming inserts; Cloud Storage; Dataproc; and Cloud Composer (Apache Airflow).
• Proficiency in Python, Scala, or Java, with a strong focus on optimized code for distributed computing platforms such as Spark or Beam.
• Mastery of modern analytics engineering frameworks such as dbt, dimensional data modeling, and lakehouse architectures such as Iceberg or Delta Lake.
• Robust experience building automated CI/CD pipelines such as GitHub Actions or GitLab CI and managing infrastructure using Terraform.

Responsibilities

• Design, implement, and monitor high-throughput, fault-tolerant streaming pipelines that ingest and process healthcare data events, including live telemetry, HL7 feeds, and ADT messages.
• Build and maintain scalable, secure, and cost-effective cloud data infrastructure using Google Cloud healthcare-native tools and Infrastructure as Code.
• Enforce healthcare security and compliance requirements, including HIPAA, HITRUST, and SOC2, through data lakehouse architectures with PHI/PII masking, role-based access control, and encryption at rest and in transit.
• Build streaming data ecosystems supporting healthcare interoperability, including real-time data catalogs and schema registries.
• Write modular, reusable, performance-tested code; lead code reviews and establish standardized CI/CD automated deployment workflows.
• Establish and champion SLAs for clinical data delivery, automated data-quality testing, and proactive system monitoring and alerting.
• Collaborate with Data Architects, Clinical Product Managers, and AI/ML teams to translate healthcare requirements into technical blueprints.
• Mentor mid-level engineers.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed