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Position :: MongoDB Data Modeler / Analytics Data science and IOT Lead Location : McLean, VA (Day 1 Onsite 3 days onsite 2 days Remot Your Impact: Meet with stakeholders to understand and document requirements which are the basis for the model solutions Provide training and mentorship, and work closely with product analysts on the product teams, on data mapping Develop model solutions, and be able to convey the pro's and con's of alternatives Review model solutions crafted by the team members to ensure alignment to standards and consistency with Industry standards and best practices Ensure consistency between the MongoDB collections Ensure maintenance of controls, data exchange management Ensure/lead model reviews to ensure fit for use (satisfies requirements, both immediate and likely future) Ensure modeling team meets all commitments and uphold the motto of "no delays to product teams" 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. Achieve data standardization for critical value sets through acquiring agreement and buy-in from stakeholders and enabling compliance through a streamlined process 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. Support data governance work as needed. Responsibilities: Designs, implements, and documents data architecture and data modeling solutions, which include the use of MongoDB and other NoSQL databases. 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 Oversee and govern the expansion of existing data architecture and the optimization of data query performance via best practices. Implement business and IT data requirements through new data strategies and designs across all data platforms (relational, dimensional, and NoSQL) and data tools. Work with business and application/solution teams to implement data strategies, build data flows, and develop conceptual/logical/physical data models. Define and govern data modeling and design standards, tools, best practices, and related development for enterprise data models. Identify the architecture, infrastructure, and interfaces to data sources, tools supporting automated data loads, security concerns, analytic models, and data visualization. Skills needed: 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 Specialized technical knowledge of the MongoDB platform or similar NoSQL technologies Experience with data warehouse, data lake, and enterprise big data platforms in multi-data-center contexts required. Good knowledge of metadata management, data modeling, and related tools (Erwin or ER Studio or others) required. Design and development experience building a reusable REST API model/framework to consume data from and/or push data into MongoDB (or similar technology) In depth knowledge of modeling/architectural patterns, governance methodologies, and potential limitations within MongoDB Ability to configure schema and MongoDB data modelling Experience in Database security management Knowledge of MongoDB administration and installation in AWS and Red Hat In-depth understanding of MongoDB architecture Excellent communication skills; ability to communicate with various stakeholders at various levels.