R&D Data Modeler Manager

Main responsibilities:

• Engage in data management and analytics projects; understand, advise, and execute on data flow optimization (e.g., data capture, integration and use across R&D)

• Understand the data-related needs for various cross-R&D capabilities (E.g., data catalog, master data management etc) and associated initiatives

• Design conceptual and logical data models and data dictionaries/ontologies to cater to R&D business needs and functional requirements; lead validation of physical data models

• Interact with business, R&D Digital, and other data collaborators to translate needs into data solutions

• Understand market trends for data modelling tools and metadata management capabilities; provides input into selection of tools and any necessary migration into company’s environment

• Understand data governance policies, standards and procedures for R&D data

• Serve as point of contact for data integration topics within solutions (e.g., technology), from source systems to data consumers; define process, tools, and testing requirements

• Maintain modelling and naming standards, and data harmonization, metadata management, and source-to-target data mapping documentation

• Evaluate and influence projects while serving as “voice-of-business”; map systems/interfaces for data management, set standards for future state, and close gap from current-to-future state

• Serve as technical and data consultant for R&D initiatives with major platforms/technology implementations

• Maintain documentation and act as an expert on data definitions, data standards, data flows, legacy data structures / hierarchies, common data models, data harmonization etc. for R&D functions

• Educate and guide R&D teams on standards and information management principles, methodologies, best practices, etc.

Deliverables

• Conduct requirements gathering from business analysts, data scientists, and other stakeholders

• Formulate strategies, and query optimizations to enhance data retrieval speed

• Develop complex and scalable data models aligned to organization’s long term strategic goals

• Formulate data governance frameworks, policies, and standards

• Establish best practices for data modeling ensuring interoperability among systems, applications & data sources

2. About you 

• Experience:5+years of experience in business data management, information architecture, technology or other related field
  

• Functional skills:

• Demonstrated ability to understand end-to-end data use and business needs

• Knowledge of R&D data and data domains (e.g., across research, clinical, regulatory etc)

• Experience with creating and applying data modelling (conceptual, logical and physical) best practices and naming conventions

• Strong analytical problem-solving skills

• Demonstrated strong attention to detail, quality, time management and customer focus

• Excellent written and oral communications skills

• Strong networking and negotiating skills to collaborate and influence stakeholders in building and managing R&D level data domain structures using best practices

• Demonstrated willingness to make decisions and to take responsibility for such

• Excellent interpersonal skills (team player)

• Technical Skills 

• Experience with data management practices and technologies (e.g., Collibra, Informatica etc)

• Familiar with databases (relational, dimensional, NoSQL, etc) and concepts of data integrity

• Strong knowledge of data architecture (e.g., data lake, data virtualization, hubs etc) and modelling (e.g., 3nf etc) is required

• Experience in big data infrastructures (E.g., Hadoop, NOSQL etc)

• Experience with SDLC and pharma R&D platforms; experience with requirements gathering, system design, and validation/quality/compliance requirements

• Experience managing technology and/or data warehouse projects

• Familiarity with relationship databases and entity-relationship data modelling

• Experience with hierarchical data models from conceptualization to database optimization

• Education: Bachelor’s in Computer Science, Engineering, Mathematics, Statistics, or related; Masters preferred

• Languages: English

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