Sr. Data Architect

Responsibilities: Design, develop, support, and maintain enterprise data and analytics frameworks and data-related applications to support cross-business functions and domains. Work within regulatory guidelines and industry best practices to drive effective collaboration across information technology and relevant business functions. Work with data modeling techniques such as hierarchical, relational, object oriented, entity-relational, dimensional, and graph, and data principles, including 1NF, 2NF, and 3NF. Administer, develop, and establish best practices for Informatica SaaS data integration solution (IICS), and define enterprise data architecture framework, standards, and principles across different data domains. Work with data and analytics applications such as cloud data solutions, data pipelines, analytics platforms, and data governance applications and catalogs. Work with Agile operating models such as Scrum, kanban, and Scrum-Ban. Analyze business requirements and author technical specifications for data solutions, including data pipelines, data models, integrations, transformations, and data marts and warehouses and ensure data and analytics solutions align with enterprise architecture principles and business strategy direction. Design and develop data engineering solutions, balancing business needs and technical implementation details to satisfy requirements and identify opportunities to improve the quality and reliability of data assets. Subject matter expert for assigned technical areas. Facilitate knowledge sharing and creative problem solving with affected business functions. Serve as a leader and change agent across information technology and cross-functional project teams. Drive continuous improvement and innovation within information technology, identifying necessary changes and facilitating updates.

Salary: $180,000-$185,000

Requirements: Bachelor’s degree in computer science, computer engineering, mechanical engineering or a related field and 6 years experience in data architecture and management for information technology. Experience must include 5 years each of the following: data modeling techniques including hierarchical, relational, object oriented, entity-relational, dimensional, and graph; defining enterprise data architecture framework, standards, and principles across different data domains; Agile operating model Scrum, kanban, or Scrum-Ban; analyzing business requirements and authoring technical specifications for data solutions, including data pipelines, data models, integrations, transformations, and data marts/warehouses; designing and developing data engineering solutions; and managing multi-functional and multi-site teams and projects. Experience must include four years pharmaceutical concepts such as GxP and validation. Experience must include two years administering, developing in, and establishing best practices for data engineering using an enterprise platform such as Informatica SaaS (IICS) or a similar solution. Experience may be gained concurrently.

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