Principal Data Architect​/Engineer - R&S

Minimum Education

Bachelor's degree or equivalent experience

Minimum Education:

Bachelor's degree or equivalent experience

Minimum Experience:

8

Directs the process for and/or participates in defining, visualizing, designing and/or developing data architecture, platforms, metadata, models (e.g., meta models, conceptual, logical, physical), strategy, and/or roadmaps. Models relationships between concepts represented by data (e.g., meta models for metadata). Owns and/or participates in strategic thought leadership, market analysis, technical assurance, and data governance related to the development, evolution and delivery of the information architecture domain as aligned to the business.

Provides context and perspective in evaluation and design beyond the immediate and stated scope of work. Collaborates with delivery teams to participate in solution design (as part of data extraction, load, and transformation, as well as for data analysis, storage, and processing solutions) or artificial intelligence solutions and directs the process to and/or independently designs data-related portions of the Dev Ops pipeline.

Shows subject matter expertise in data architecture and related disciplines. Works with teams as a subject matter expert in this area to enable and improve solution design and delivery around data.

• Independently creates and documents standards, design patterns, and best practices for data-related software development, incorporating appropriate constraints (e.g., data management best practices, information security such as access enforcement based on data sensitivity, systems controls, systems monitoring, regulatory constraints such as data retention, etc.). Directs the process for and/or participates in visualizing and designing the enterprise data management framework based on industry best practices (such as Data Management Body of Knowledge, DMBoK).
  
  Has expert knowledge of system development lifecycle, system maintenance, and system security. Directs and/or contributes to designing data-related portions of the Dev Ops pipeline (e.g., data model and database changes, data pipeline and automation) as an enabler for solution delivery team process. Decides the process for and participates in documenting information and data flow within the context of business processes or defined business outcomes, capturing required behaviors of the data based on end user feedback (including which parts of the organization generate and consume data, allowable values and conditionality, entity states, etc.).
• Directs the process for and/or participates in visualizing and designing the enterprise data management framework based on industry best practices (such as Data Management Body of Knowledge, DMBoK). Develops strategies to improve performance of data through advice on technology selection; data structure or layout; architectural choices; or other best practices. Has expert knowledge of system development lifecycle, system maintenance, and system security.
• Directs and may make the final decisions for and/or participate in defining data architecture frameworks and standards in alignment with enterprise data management principles and guidance, including data modeling (e.g., meta models, conceptual, logical, physical), metadata management, data security, reference data such as product codes and client categories, and master data such as clients, vendors, materials, and employees. Has expertise in using version control and Agile best practices for the delivery of data in a Dev Ops pipeline using tools such as git, CI/CD, etc.
  
  Directs vertical alignment and integration analysis among different types of architectures including business architectures, data architectures, application architectures and technology architectures.
• Directs the process for and/or participates in conducting data extraction, ingestion, and loading to transform data to be accessible by users. Has expert knowledge of data warehouse and lake architecture, data file types, data delivery methods, ETL tools, data pipeline and automation, data management systems, data storage…