We are Intel : We create world-changing technology that enriches the lives of every person on earth.The Opportunity Ahead : Intel is on a multi-year data and digital transformation journey to unlock the full potential of better, faster, and interoperable data to accelerate business value at a torrid pace.
The enterprise Data and Analytics data architect will be part of the Data Architecture team of the recently established enterprise data and analytics architecture and governance organization.
This organization has a significant cross-Intel impact and focuses on providing a data advantage to Intel from data strategy and governance to execution and improving business outcomes.
This position needs solid data architecture innovation and execution mindset and needs to be recognized as a trustworthy advisor in their domain expertise and responsibility by technologists and principal engineers across multiple organizations, and respected by peers in both business and IT.
The position has a solid player role i.e., significant individual contribution scope, and collaborate with high-performing enterprise data domain architects to deliver connected / assured data assets at Intel.
Responsibilities include, but will not be limited to : Lead and drive all aspects of Data and Analytics architecture for one or more domains areas under supply chain, product engineering, sales and marketing, manufacturing, finance / legal, etc.
Provide thought leadership and hands-on technical data architecture and data modelling expertise by partnering with cross-functional IT and business stakeholders and ensure compliance with Intel's data architectural principles and data governance policy.
Develop and promote modern data architectural approaches that ensure connected data and digitized processes, end-to-end business connectivity, and encourage cross-functional collaboration across business units.
Maintain a big picture view and participate in data architecture design assurance forums / councils with solution architects, data architects, business architects, and principal engineers to ensure cross-domain and cross-function architectural alignment for their data domain and overall cohesive data ecosystem.
Ensure business rules, data definitions, and functional aspects are captured accurately and appropriately within data models.
Engage with Business / Data stewards in creation and / or maintenance of business glossary for the respective subject area.
Communicate technical solutions to business partners in a meaningful way.Conduct comprehensive cost / benefit, fit gap, and pro / con analysis.
Follow, role-model, and mentor mature software development lifecycle associated with agile methodology - such as requirements gathering and assessment, backlog management and prioritization, software build, validation, test, path to production, quality, and support.
Mentor and educate more junior data architecture team members.In addition, the ideal candidate should also exhibit the following behavioral traits : Self-starter with solid business acumen who understands organizational issues and challenges.
Entrepreneurial multi-tasker who can be highly efficient with ambiguity and complexity and enjoys being willing to navigate changing direction of projects and strategies.
Skills to understand the culture and emotional blockers for people's willingness to embrace change.Strategic thinking and act operationally.
Exceptional analytical, written, oral, and presentation skills.
Minimum qualifications are required to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.
Minimum Qualifications : Bachelor's degree, MBA or Master's degree in Computer Science, Computer Engineering or any other related field (focus on data and analytics is preferred).
7+ years of experience in Data and Analytics architecture, and data lake / data warehousing with emphasis on enterprise-scale supply chain and product data scope.
knowledge of modern techniques such as data vault or knowledge graph data models, data fabric. Data governance solutions such as metadata management, data cataloging solutions, data integration, data quality, master, and reference data management.
including emerging data modeling techniques such as NoSQL, architectural frameworks such as TOGAF or Zachmann.