About The Position
We're seeking a Principal Engineer to establish data architecture excellence across our engineering organization. As we transition to autonomous, stream-aligned teams, we need a hands-on data expert who can enable application teams to make sound data decisions independently. This role works side-by-side with application engineers, not in isolation. Your peers will be full-stack and backend engineers building products. You need to understand application architecture, API design, and deployment practices - and bring deep data expertise to that context. What We're Looking For You come from an application development background and understand how data fits into the broader application architecture. You're hands-on and take ownership - you can architect complex data systems and roll up your sleeves to optimize them. You succeed by making others successful - you educate and empower rather than gatekeep. You speak the language of application engineers and can review their code, understand their challenges, and guide them to better data solutions. You understand trade-offs, know when to optimize for speed vs. perfection, and can influence without authority. You've run data systems in production at scale and understand what it takes to keep them performant and reliable. Why This Role Matters GHX Engineering is transforming toward autonomous, stream-aligned teams with independent deployment capabilities. This role is central to that vision - establishing data architecture excellence that enables teams to move fast without creating future problems. You'll define data strategy for a growing engineering organization in healthcare technology, working directly with engineering leadership on this transformation.
Requirements
- 10+ years building software applications with heavy focus on data systems
- Strong application development background (full-stack, backend, or data-intensive applications)
- Deep expertise in NoSQL (MongoDB, DynamoDB, DocumentDB) and relational databases (PostgreSQL, SQL Server)
- Proven experience optimizing database performance at scale (query tuning, indexing, resource management)
- Strong data modeling and schema design skills
- Understanding of application architecture, API design, and software development practices
- Deep experience with cloud data platforms (AWS, Azure, or GCP) including cost optimization
- Experience with AI/LLM-assisted development tools and agentic software engineering practices
- Track record of establishing data standards across engineering organizations
- Excellent communication skills - able to influence and educate engineers at all levels
Nice To Haves
- Experience as a full-stack or backend engineer with deep data focus
- Proficiency in Python, Java, JavaScript/TypeScript, or C#
- AWS data services (RDS, Aurora, Redshift), Snowflake, or modern data warehouses
- Advanced data modeling (temporal models, event sourcing, complex domain modeling)
- Healthcare or EDI domain knowledge
- Experience with event-driven architectures and change data capture
- ETL/ELT tools and data pipeline orchestration
- Prior Principal/Staff Engineer experience
Responsibilities
- Work directly with application teams on data architecture for their applications and services
- Design and review data architectures and models, aligning data ownership with team domain boundaries
- Review application code and architecture with focus on data access patterns and performance
- Evaluate and recommend data storage technologies (MongoDB, PostgreSQL, NoSQL, document stores, warehouses)
- Optimize database performance: query tuning, indexing, execution plan analysis, resource management
- Guide technology selection based on read/write patterns, data volumes, and access patterns
- Define data access patterns: APIs, ORMs, event-driven architectures, replication strategies
- Establish data replication and syndication strategies (CDC, event streaming, batch processing)
- Guide data architecture for ML/LLM applications (vector databases, embeddings, RAG patterns)
- Lead zero-downtime data migrations and infrastructure modernization
- Hands-on troubleshooting and optimization of critical data systems
- Establish data quality, monitoring, and observability standards
- Lead knowledge sharing through workshops, documentation, and office hours
Benefits
- health, vision, and dental insurance
- accident and life insurance
- 401k matching
- paid-time off
- education reimbursement
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
