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Proficiency in MongoDB's flexible schema model, validation, access pattern recognition to design appropriate document structures (embedded and normalized models) for optimal read and write performance at scale.
Proficiency in MongoDB Advanced CRUD operation and complex aggregation pipelines.
Knowledge of Database indexing techniques and strategies to optimize and improve query performance.
Experience in MongoDB’s high availability and failover, vertical and horizontal scalability, including replica sets and sharding.
Proficiency with MongoDB Atlas, Shell, compass.
Experience and understanding of data lifecycle, architecture, modeling, metadata, lineage, profiling, monitoring, rule definition, and remediation to ensure data accuracy, consistency, and reliability during migration.
Understanding of relational database systems (SQL, schema design, import, export etc.) is crucial for migrating from traditional databases to MongoDB.
Expertise in ETL/ ELT processes and tools.
Strong understanding of Kafka Design patterns is nice to have.
boot frameworks.
Expert Knowledge in any of these cloud platforms (AWS, Google Cloud) and cloud migration strategies.
Implementing security best practices, including authentication and encryption (At rest, In transit). experience in multiple options in securing data within a healthcare organization (PHI, PII, and PCI).
Good understanding of Mark Logic database and XQuery.
Knowledge of previous healthcare data experience (members, providers, and claims) is most desired.
Problem-Solving: Analytical thinking and the ability to diagnose and resolve technical challenges.
Communication: Clearly communicating complex technical concepts to technical and non-technical stakeholders, creating documentation, and coordinating with different teams.
Leadership: Demonstrates accountability and leadership in driving the program targets and influences the team/stakeholders towards the target.