IT Data Modeler (Hybrid)

IT Data Modeler (Hybrid)Our Team:The IT Data Modeler plays a crucial role in designing, developing, and maintaining data models to support efficient data management and analytics within the organization. This role is essential in optimizing data architecture, translating business initiatives into robust data models, and enhancing data integrity, availability, and performance. The data modeler is responsible for developing conceptual, logical, and physical data models. The data modeler role is key to enabling business intelligence, artificial intelligence, machine learning, data science, data warehouse and other business interests.Essential Functions:Design, create, and implement logical and physical data models for both IT and business solutions to capture the structure, relationships, and constraints of relevant datasets.Build and operationalize complex data solutions, correct problems, apply transformations, and recommend data cleansing/quality solutions.Effectively collaborate and communicate with various stakeholders to understand data and business requirements and translate them into data models.Create entity-relationship diagrams (ERDs), data flow diagrams, and other visualization tools to represent data models.Collaborate with database administrators and software engineers to implement and maintain data models in databases, data warehouses, data lakes, and data flows.Define and govern data modeling and design standards, tools, best practices, and use these standards to identify and resolve data modeling issues and conflicts.Conduct performance tuning and optimization of data models for efficient data access and retrieval.Identify the architecture, infrastructure, and interfaces to data sources, analytic models, and data visualization.Incorporate core data management competencies, including data governance, data security and data quality.Evaluate data models for variances, discrepancies to improve efficiency and aligning with standards.Review existing source systems or database to reverse engineer into data models.Technical Knowledge/Skill/Education/Licenses/Certifications:Technical Knowledge/Skill:Expert knowledge of data modeling concepts, methodologies, and best practices.Proficiency in data modeling tools such as Erwin or ER/Studio.Knowledge of relational databases and database design principles.Experience with data warehouse, data lake, and enterprise data platforms in Cloud technologies is preferred.Experience in data querying, manipulation, and optimization, and knowledge of other data science languages, including JavaScript, Python, or R is desired.Ability to collaborate with cross-functional teams and stakeholders to gather requirements and align on data models.Excellent analytical and problem-solving skills to identify and resolve data modeling issues.Strong communication and documentation skills to effectively convey complex data modeling concepts to technical and business stakeholders.Work proactively to address project requirements and articulate issues/challenges to reduce project delivery risks.Education:

A bachelor’s degree in computer science, data science, software engineering, or related field.Experience :At least three years of experience in data modeling, database design, or related fieldHands-on relational, dimensional, and analytical project experience using RDBMS, data platform technologies, ETL and data ingestion protocols.Working Conditions:Must be available to work emergency restoration assignment as required.Must be available to travel between MA/CT/NH as necessary.

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