Senior Data Engineer (AI)

Location: Chicago, United States

Salary: $125,000–$180,000 annually for Chicago; the range may vary by location.

Company

hirify.global develops a precision-medicine platform that connects real-world healthcare evidence with AI-powered clinical insights.

What you will do

• Build production pipelines for structured and unstructured EHR, genomic, and cardiovascular imaging data.
• Own BigQuery warehouses, dbt transformations, data models, testing, documentation, and SQL standards.
• Develop event-driven Pub/Sub services with retries, idempotency, ordering, and dead-letter handling.
• Create metadata, retrieval, and data-access layers that enable AI agents to discover and reason over clinical datasets.
• Build TypeScript services and APIs for agent inputs, outputs, and coordination.
• Operate Google Cloud infrastructure with Terraform across BigQuery, Pub/Sub, Cloud SQL, Cloud Storage, Memorystore, Secret Manager, IAM, and service accounts.

Requirements

• 5+ years building production data-intensive software systems, including 3+ years in data engineering, pipeline ownership, or data modeling.
• 2+ years designing and operating Google Cloud workloads and 2+ years in HIPAA-regulated healthcare environments with Epic or Cerner integrations.
• Strong Python, TypeScript, SQL, dbt or equivalent transformation-framework, and production software-engineering experience.
• Experience with event-driven or queue-based architectures, structured and unstructured data at million-record scale, and data quality and lineage.
• Working knowledge of HL7, FHIR, DICOM, genomic data formats, and familiarity with HIPAA and SOC 2 security requirements.
• 1+ year building with large language models, agentic workflows, retrieval-augmented generation, or autonomous tool use; a bachelor's degree or equivalent professional experience.

Nice to have

• Experience with Google Cloud Healthcare API, managed FHIR or DICOM stores, OMOP, genomic data models, or longitudinal patient records.
• Kubernetes experience and exposure to vector or graph databases such as Pinecone, Weaviate, or pgvector.
• AWS experience in multi-cloud environments and advanced modeling methods such as Data Vault 2.0 or Master Data Management.

Culture & Benefits

• High ownership of systems from development through production operations.
• Self-directed work in an early-stage platform with an open problem space.
• Close collaboration with clinical, analytics, and platform engineering partners.
• Benefits may include incentive compensation, restricted stock units, medical coverage, and other benefits depending on the position.