Need database specialist

We'd need some help from a database specialist to work an existing financial platform with large records of companies and contacts. The Challenge: We are experiencing severe latency issues specifically tied to contact record updates within our CRM. When users add or update contact records, there is a significant delay before the data is persisted to the database and reflected in the UI. This write-latency is impacting user productivity and data reliability across the platform. We are looking for a specialist to diagnose the root cause and implement a robust, lasting solution. Scope of Work: Conduct a deep-dive audit of our database architecture, query patterns, and application-layer data flow for contact/CRM-related operations. Identify bottlenecks causing write-latency (e.g., missing indexes, lock contention, inefficient ORM queries, transaction scope issues, replication lag, cache invalidation delays, or connection pool exhaustion). Profile and optimize slow queries, schema design, and indexing strategies for high-volume contact and conversation records. Review and optimize our caching layer (e.g., Redis/Memcached) and cache-invalidation logic to ensure updates are reflected immediately. Audit background job queues and async processing pipelines that may be delaying persistence or display updates. Implement monitoring, alerting, and observability for database performance and query execution times. Deliver documentation and knowledge transfer so our team can maintain performance gains. Required Skills & Experience: 7+ years of backend engineering experience with a heavy focus on database performance and optimization. Deep expertise in relational databases (PostgreSQL, MySQL, or SQL Server): query planning, execution plans, indexing strategies, partitioning, and transaction isolation levels. Proven track record diagnosing and fixing write-latency and read-replication lag in high-traffic web applications. Strong experience with ORM optimization (e.g., Django ORM, SQLAlchemy, TypeORM, Hibernate, Entity Framework) and eliminating N+1 queries. Hands-on experience with caching architectures and real-time data sync patterns (cache-aside, write-through, WebSockets, server-sent events). Proficiency in our backend stack (or similar): [insert your stack, e.g., Python/Django, Node.js/Express, Ruby on Rails, .NET, Java/Spring]. Experience with observability tools (Datadog, New Relic, Prometheus/Grafana, AWS CloudWatch, pg_stat_statements). Nice-to-Have: Experience with CRM platforms, financial data systems, or marketplace applications. Familiarity with CQRS, event sourcing, or eventual consistency patterns. Knowledge of database migration strategies for large datasets with minimal downtime. Full-stack capability to audit frontend data-fetching patterns if display latency is client-side.