Overview
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 You'll Do
- 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
Required Qualifications
- 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
Preferred Qualifications
- Experience as a full-stack or backend engineer with d