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6.0 - 10.0 years

0 Lacs

pune, maharashtra

On-site

As a MongoDB Physical Data Modeller, your primary responsibility will be to develop high-quality Physical Data Models by analysing and translating Logical Data Models (LDMs) into practical, scalable schemas. You will closely work with business analysts and data architects to interpret LDMs, ensuring a deep understanding of entity relationships, dependencies, and attribute definitions. Collaborating with cross-functional teams, you will gather requirements, align data models with business needs, and ensure data quality. Additionally, you will design, optimise, and implement efficient data models in MongoDB, ensuring they meet performance and storage requirements. Being the bridge between database management, development, and infrastructure teams, you will ensure that the data model aligns with application requirements and infrastructure limitations. Maintaining comprehensive documentation of all Physical Data Models, schema changes, and MongoDB configurations will also be part of your responsibilities. You should have demonstrable hands-on experience in designing, deploying, and managing MongoDB Physical Data Models that support large-scale applications. Strong knowledge of MongoDB concepts, including schema design, index strategies, and query optimization is essential. Proficiency in document-oriented database design, data normalization, and denormalization techniques specific to MongoDB is required. You should also be detail-oriented with strong analytical skills and the ability to work independently and collaboratively. Preferred skills for this role include experience with other NoSQL databases or data modelling tools, familiarity with industry standards in data modelling and database design, and knowledge of industry-standard data modelling practices. Additionally, expertise in MongoDB tools such as Compass and Atlas, data modelling software, and MongoDB performance tuning, backup, and recovery strategies would be beneficial. Your role will also involve providing insights and recommendations for MongoDB schema design improvements and enhancements, as well as guiding junior team members and stakeholders on best practices in MongoDB data modelling and usage to foster a deeper understanding across the organization.,

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