Description

Key Responsibilities

• Design and define enterprise-level database architectures, standards, patterns, and best practices
• Evaluate and select relational, NoSQL, and cloud-native database technologies based on business and technical requirements
• Design scalable solutions covering data modeling, availability, resiliency, backup/recovery, replication, and disaster recovery
• Optimize database performance through query tuning, indexing, partitioning, and capacity planning
• Establish database security standards including encryption, access controls, auditing, and compliance
• Use Python for database automation, scripting, data processing, and validation
• Provide architectural guidance for AI-related data patterns including embeddings, vector databases, and RAG
• Create and maintain architecture diagrams, technical documentation, and design decisions
• Mentor and provide technical leadership to engineering teams

Required Skills

• Strong experience in database architecture, engineering, or administration
• Deep expertise in relational database concepts: SQL, data modeling, normalization, indexing, transactions, performance optimization
• Hands-on experience with one or more: PostgreSQL, Oracle, SQL Server, MySQL, MongoDB
• Hands-on experience with AWS, Azure, or GCP managed database services
• Experience with database migration and modernization initiatives
• Basic to intermediate Python skills for scripting and automation
• Understanding of AI, ML, and Generative AI concepts

Preferred Skills

• Experience with cloud-native and distributed database architectures
• Infrastructure as Code and DevOps/CI/CD practices
• Database observability, monitoring, and automated operations
• Data governance, security, privacy, and regulatory compliance experience
• Exposure to AI/ML platforms and cloud-based AI services
• Experience with vector databases, embeddings, semantic search, LLMs, and RAG
• Background supporting large-scale, high-volume enterprise systems

Key Skills

Education

Bachelor's degree