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Meet with stakeholders to understand and document requirements which are the basis for the model solutions
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Provide training and mentorship, and work closely with product analysts on the product teams, on data mapping
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Develop model solutions, and be able to convey the pro's and con's of alternatives
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Review model solutions crafted by the team members to ensure alignment to standards and consistency with Industry standards and best practices
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Ensure consistency between the MongoDB collections
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Ensure maintenance of controls, data exchange management
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Ensure/lead model reviews to ensure fit for use (satisfies requirements, both immediate and likely future)
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Ensure modeling team meets all commitments and uphold the motto of "no delays to product teams"
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Ensure continued creation/maintenance of critical modeling artifacts, ex. requirements and modeling analysis documentation, model change requests logs, data dictionaries, artifacts for architecture document, etc.
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Achieve data standardization for critical value sets through acquiring agreement and buy-in from stakeholders and enabling compliance through a streamlined process
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Identify and document patterns, especially in domain and enterprise models, ensuring alignment and/or ease for integration (common language), and escalate blockers to Sr. Manager.
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Support data governance work as needed.
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Designs, implements, and documents data architecture and data modeling solutions, which include the use of MongoDB and other NoSQL databases.
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Development of the conceptual, logical, and physical data models, the implementation of RDBMS, operational data store (ODS), data marts, and data lakes on target platforms (SQL/NoSQL).
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Oversee and govern the expansion of existing data architecture and the optimization of data query performance via best practices.
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Implement business and IT data requirements through new data strategies and designs across all data platforms (relational, dimensional, and NoSQL) and data tools.
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Work with business and application/solution teams to implement data strategies, build data flows, and develop conceptual/logical/physical data models.
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Define and govern data modeling and design standards, tools, best practices, and related development for enterprise data models.
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Identify the architecture, infrastructure, and interfaces to data sources, tools supporting automated data loads, security concerns, analytic models, and data visualization.
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8-10 years data modeling experience with 5+ years of hands-on relational, dimensional, and/or analytic experience (using MongoDB and other NoSQL data platform technologies, and ETL and data ingestion protocols).
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Specialized technical knowledge of the MongoDB platform or similar NoSQL technologies
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Experience with data warehouse, data lake, and enterprise big data platforms in multi-data-center contexts required.
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Good knowledge of metadata management, data modeling, and related tools (Erwin or ER Studio or others) required.
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Design and development experience building a reusable REST API model/framework to consume data from and/or push data into MongoDB (or similar technology)
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In depth knowledge of modeling/architectural patterns, governance methodologies, and potential limitations within MongoDB
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Ability to configure schema and MongoDB data modelling
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Experience in Database security management
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Knowledge of MongoDB administration and installation in AWS and Red Hat
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In-depth understanding of MongoDB architecture
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Excellent communication skills; ability to communicate with various stakeholders at various levels.