Mongodb Expert

Data Modeling and Schema Design: Understanding MongoDB's flexible schema model and how to design appropriate document structures (embedded and normalized models) for optimal performance and scalability. Knowledge of healthcare data (members, providers, and claims) is most desired

Querying and Aggregation: Proficiency in MongoDB Query Language (MQL) and the Aggregation Framework for efficient data retrieval and transformation.

Indexing: Knowledge of different index types and how to optimize indexes for improved query performance.

Replication and Sharding: Understanding of MongoDB's high availability and scalability features, including replica sets and sharding.

MongoDB Tools: Familiarity with MongoDB tools like Compass, Atlas, and native tools (mongodump, mongorestore) with a particular emphasis on Atlas.

Relational Database Knowledge: Understanding of relational database systems (SQL, schema design, etc.) is crucial for migrating from traditional databases to MongoDB.

ETL Processes: Expertise in Extract, Transform, Load (ETL) processes and tools.

Data Quality and Validation: Implementing data quality rules, validation techniques, and ensuring data consistency during migration.

Programming and Scripting: Proficiency in languages like Python , JavaScript, Springboot for migration scripts and automation. Experienced in development using Microservices Architecture and Springboot frameworks.

Cloud Technologies: Expert Knowledge in any of these cloud platforms (AWS,Google Cloud) and cloud migration strategies

Data Security: Implementing security best practices, including authentication and encryption. Knowledge of the options to secure data within a healthcare organization (PHI, PII, and PCI)