Mongodb architect

As a MongoDB Architect, your role involves collaborating with stakeholders to understand their data needs and developing a MongoDB strategy aligned with the organization's overall data goals. Your key responsibilities include: - Defining and implementing data governance policies and procedures specifically for MongoDB data to ensure data quality, consistency, and compliance with regulations. - Designing and documenting the MongoDB architecture, including data models, data flows, sharding strategies, replication setups, and indexing plans. - Evaluating and recommending appropriate MongoDB tools and technologies to optimize performance and management. - Creating and maintaining data models for MongoDB to represent data effectively and efficiently. - Deploying, configuring, and managing MongoDB instances for high availability, scalability, and data resilience. - Analyzing MongoDB performance, identifying bottlenecks, and implementing solutions to improve query performance and efficiency. - Implementing security measures for MongoDB to protect sensitive data and comply with regulations. - Integrating MongoDB with cloud platforms like AWS, Azure, or GCP for scalability and enhanced manageability. - Monitoring MongoDB instances, tracking performance metrics, and addressing any issues proactively. - Designing and managing data pipelines that integrate MongoDB with other data sources and systems. - Planning and managing MongoDB capacity to meet current and future data growth. - Collaborating effectively with stakeholders to communicate MongoDB architecture plans and ensure alignment. - Staying updated with the latest MongoDB features, best practices, and industry trends. - Participating in Agile Scrum planning, estimation, and sprint execution. Qualifications required for this role: - Deep understanding of MongoDB architecture, including document-oriented data model, sharding, replication, and indexing. - Proficiency in creating effective schema structures, data relationships, and optimizing queries. - Strong skills in analyzing performance bottlenecks and implementing solutions. - Technical foundation in data warehousing, data modelling, data integration, and data governance principles. - Familiarity with security best practices, access control mechanisms, data encryption, and backup/recovery strategies.,