Senior Database Architect

This is a fully remote position, open to applicants in California, +3 more states.

📋 Description

• Analyze and break down extensive SQL Server stored procedures featuring integrated business logic.

• Develop migration plans that extract business logic into domain services.

• Create design patterns that distinguish business rules from data access.

• Lead refactoring efforts in accordance with domain-driven design, bounded contexts, aggregates, and domain events.

• Implement change data capture, outbox, and event-sourcing patterns as needed.

• Enhance queries, indexing strategies, and execution plans for improved performance.

• Develop migration playbooks and tools for modernizing stored procedures.

• Design semantic data models to facilitate AI retrieval and reasoning.

• Architect solutions for vector databases and RAG implementations.

• Design and execute embedding pipelines.

• Establish patterns for knowledge graphs, entity relationships, ontologies, and graph-based retrieval.

• Define data architectures aimed at ensuring AI-agent context, freshness, and consistency.

• Design RAG evaluation frameworks that assess retrieval accuracy, relevance scoring, and continuous improvement.

• Create canonical data models and schemas across SQL Server, PostgreSQL, MongoDB/Cosmos DB, Snowflake, and vector databases.

• Architect Kafka-based event streaming, materialized views, CQRS, and real-time synchronization solutions.

• Set up data pipelines, ETL/ELT orchestration, data quality, and observability patterns.

• Define strategies for data residency, partitioning, and multi-region deployment.

• Create reference architectures to guide domain teams.

• Utilize AI coding assistants to expedite database modernization efforts.

• Develop AI-powered tools for database engineering.

• Generate AI-consumable documentation, annotated schemas, and context files.

• Author skills for database architecture to facilitate AI-assisted development.

• Develop prompts, workflows, and tools to support AI-enabled modernization initiatives.

• Collaborate with AI/ML teams, domain teams, and application architects.

• Contribute to the standards set by the Enterprise Architecture Council.

• Mentor engineers in areas such as database design, optimization, semantic modeling, and AI data infrastructure.

⛳️ Requirements

• 8–12 years of experience in database engineering and architecture, particularly in enterprise-scale SQL Server environments.

• Profound expertise in SQL Server, including T-SQL optimization, stored procedure design and refactoring, query plan analysis, indexing strategies, and performance tuning.

• Hands-on experience in modernizing complex stored procedures and migrating business logic to application services.

• Experience designing solutions across SQL Server, PostgreSQL, MongoDB, Cosmos DB, Snowflake, and data lakehouse platforms.

• Practical experience with CDC, Kafka, outbox patterns, event sourcing, and CQRS.

• Expertise in data modeling, including canonical models, dimensional modeling, schema evolution, and extensibility.

• Hands-on experience with at least one vector database, such as Pinecone, Weaviate, Milvus, pgvector, Azure AI Search, or similar.

• Understanding of RAG architecture, embedding models, chunking strategies, retrieval optimization, hybrid search, and reranking patterns.

• Experience in designing semantic data structures optimized for AI retrieval, knowledge representation, ontologies, or domain-specific AI schemas.

• Familiarity with embedding pipelines, including text preprocessing, embedding generation, vector indexing, and incremental updates.

• Understanding of LLM context requirements, token constraints, and context window optimization.

• 2+ years of active use of AI coding assistants for database tasks, such as GitHub Copilot, Cursor, or Claude Code.

• Experience in creating tools, scripts, or automation that leverage AI/LLM functionalities.

• Familiarity with structured artifacts for AI consumption, including documented schemas, annotated procedures, and context files.

• Strong programming skills in at least one backend language, such as C#, Java, or Python.

• Experience with cloud data services, including Azure SQL, Cosmos DB, Azure AI Search, Azure Synapse, Snowflake, or AWS equivalents.

• Experience in infrastructure-as-code using Terraform, ARM/Bicep, or CloudFormation.

• Understanding of domain-driven design and bounded contexts.

• Familiarity with data governance, lineage, and compliance requirements, including HIPAA and PCI-DSS.

• Preferred: background in healthcare, benefits, payments, or similarly regulated sectors.

• Preferred: experience in building RAG systems or AI-powered search/retrieval applications.

• Preferred: knowledge graph experience with Neo4j, Amazon Neptune, or similar graph databases.

• Preferred: contributions to database tooling, AI/ML data infrastructure, or open-source projects.

• Preferred: experience mentoring engineers or leading database/data architecture communities of practice.

🏝️ Benefits

• Health, dental, and vision insurances.

• Retirement savings plan.

• Paid time off.

• Health savings account.

• Flexible spending accounts.

• Life insurance.

• Disability insurance.

• Tuition reimbursement.

• Eligibility for quarterly or annual bonuses for non-sales roles.