Note: The job is a remote job and is open to candidates in USA. GHX is a healthcare supply chain exchange and data automation company that reliably moves transaction data among thousands of trading partners. The Principal Software Engineer will provide hands-on architectural leadership for integration, event-driven systems, APIs, data modeling, and database practices while guiding the decomposition of a large-scale monolith into independently deployable services and establishing engineering standards.
Responsibilities
- Define GHX's integration patterns: outbox, saga, CDC, event-carried state transfer, dual-write mitigation, and when to choreograph vs. orchestrate
- Guide service boundary design: where to draw domain lines, how to handle shared reference data, and how to prevent shared-database coupling between services
- Own the messaging and eventing layer: topic and queue design, schema contracts, partitioning, retention, consumer group management, dead-letter handling, replay, and operational monitoring
- Lead the architectural direction for replacing GHX's homegrown event bus with a cloud-native messaging platform, and establish the standards teams will build on after the transition
- Guide teams on streaming vs. batch trade-offs and on replacing batch- or file-driven pipelines with event-driven flows where latency and reliability require it
- Establish REST API design standards: resource modeling, versioning strategy, error contracts, pagination, and backward compatibility
- Own the API governance lifecycle: versioning policy, deprecation timelines, breaking change detection in CI/CD, schema compatibility enforcement, and consumer-driven contract testing
- Define traffic management patterns for API transitions: versioned routing, canary rollouts, and gateway configuration for safe rollout and rollback
- Guide teams on integration style selection and review service designs for evolvability and downstream interface cost
- Work with teams on schema design, data modeling, and aligning data ownership with service boundaries
- Guide datastore selection by workload: read/write patterns, consistency requirements, and cost trade-offs across relational, document, key-value, and analytical options; for NoSQL, lead access-pattern-first design including partition strategy, secondary index selection, and partition distribution
- Advise on ORM vs. raw query trade-offs and define data access standards that avoid common anti-patterns (N+1, chatty calls, unbounded result sets)
- Guide teams on performant data access and zero-downtime schema evolution: indexing strategy, backfill approaches, dual-write windows, and rollback-safe migrations
- Establish replication and syndication patterns for cross-service data movement: CDC, change streams, materialized views, and read models
- Run design reviews, workshops, and office hours to raise integration and data fundamentals across engineering
- Produce decision records, design guides, and reference implementations teams can build from
- Present architectural trade-offs and technical risk to engineering leadership, product, and senior stakeholders
Skills
- 10+ years building distributed systems, grounded in hands-on software development as an individual contributor: you have written and shipped production code and understand the day-to-day engineering reality your guidance needs to hold up against
- Deep experience with event-driven architecture and distributed systems: pub/sub and messaging infrastructure (Kafka, AWS SQS/SNS/EventBridge, or equivalents), integration patterns (outbox, CDC, saga, event sourcing), and failure modes including idempotency, consistency trade-offs, and operational failure handling
- Hands-on AWS experience with data and integration services: SQS, SNS, EventBridge, DynamoDB, RDS/Aurora, API Gateway, Lambda
- Strong data architecture fundamentals across relational and NoSQL: datastore selection by workload, schema and access-pattern design, ORM trade-offs, and performant data access at scale
- Experience designing REST APIs with attention to versioning, backward compatibility, and data contracts, including contract validation in CI/CD pipelines
- Experience working directly with application teams during service decomposition, and a track record of establishing integration and data standards across an engineering organization
- Strong communication across levels: writing clear decision records for engineering peers, presenting trade-offs to engineering and product leadership, and translating technical risk for senior stakeholders
- Heavy personal investment in AI-assisted and agentic development: your workflow has materially changed over the last 6-12 months, you use coding agents for substantial engineering work, and you have concrete examples of where these tools have made you meaningfully faster or produced better outcomes; the engineers around you tend to notice and follow
- Experience integrating with external partners or enterprise platforms (supply chain, ERP, CRM, or similar), including migrating from batch- or file-driven pipelines to event-driven flows
- Healthcare or other regulated industry experience
- Azure PaaS experience (Service Bus, Cosmos DB, Azure Functions)
- Infrastructure-as-code experience (Terraform or equivalents)
- Analytics data layer experience: Snowflake, Redshift, or similar
- Data architecture for ML/LLM applications (vector databases, embeddings, RAG patterns)
- Prior Principal or Staff Engineer experience
Benefits
- Bonus
- Health insurance
- Vision insurance
- Dental insurance
- Accident insurance
- Life insurance
- 401k matching
- Paid time off
- Education reimbursement
Company Overview
Company H1B Sponsorship