• Design and maintain standardized data schemas used across different data sources and storage systems • Define data contracts and models to ensure consistent representation of entities such as users, groups, resources, and permissions • Develop and maintain schema evolution and versioning processes to support iterative product development • Ensure data models are optimized for both transactional and analytical workloads • Collaborate with engineering and product teams to align data models with business logic and reporting requirements • Design and optimize ClickHouse schemas for analytical and time-series workloads • Maintain PostgreSQL schemas for metadata, configuration, and application-level data • Develop indexing, partitioning, and retention strategies that balance performance, scalability, and cost • Define transformation specifications to ensure consistency between raw and analytical data layers • Establish naming conventions, data types, and relationship standards for all stored data • Implement validation and normalization checks to ensure incoming data adheres to defined schemas • Partner with QA and product teams to verify that stored data accurately represents system behavior and business intent • Maintain clear documentation and metadata definitions for all datasets and structures • Manage schema migrations and versioning through CI/CD workflows • Collaborate with DevOps teams to deploy and monitor databases in Kubernetes-based environments • Use Infrastructure as Code tools (Helm, Terraform, or similar) for consistent database provisioning • Support observability and monitoring for data performance and reliability.