We are looking for a leader that can work across various teams such as Analytics, Project Management, and Technology driving Data Governance designs. This leader designs the processes and protocols to manage data effectively across the technology ecosystem in an effort to maintain quality, consistency, availability of data needed to produce the required internal analytics and dashboards more efficiently. This leader will need to work with key data domain stake holders to understand value drivers for different data attributes and characteristics, so that the correct business logic is applied, documented and executed. They also contribute crucial intellectual capital to project, analytics and business teams by designing and implementing standardized processes and protocols to enable efficient data management; they also behave like Business Analysts who understand client requirements and are able to produce clear documentation to facilitate automation of data processing. This person will report to a Vice President of IT with a preferred location of Austin or Santa Clara.

　　Skills, Knowledge, Experience & Education

　　At Applied Materials, Make Possible® is about unlocking new opportunities – with our customers and within our own company.

　　The ideal candidate will have the following:

　　Responsible for designing, creating, deploying and managing an organization's data architecture.

　　Define how the data will be stored, consumed, integrated and managed by different data entities and IT systems, as well as any applications using or processing that data in some way.

　　Ensures that an organization follows a formal data standard and that its data assets are in line with the defined data architecture and/or with the goals of the business.

　　Maintains the metadata registry, oversees data management, optimizes databases and/or all data sources and more.

　　Provides a standard common business vocabulary, expresses strategic data requirements, outlines high level integrated designs to meet these requirements, and aligns with enterprise strategy and related business architecture.

　　Expected to set data architecture principles, create models of data that enable the implementation of the intended business architecture, create diagrams showing key data entities, and create an inventory of the data needed to implement the architecture vision

　　Support operational use of data for business process functions such as customer centricity, supply chain, product positioning, sales efficiency, and other domain centric functions

　　Document data inventory and data flow diagrams to determine what can be measured, when and how

　　Key Responsibilities:

　　Responsible for designing, creating, deploying and managing an organization’s data architecture.

　　Define how the data will be stored, consumed, integrated and managed by different data entities and IT systems, as well as any applications using or processing that data in some way.

　　Ensures that organization follows a formal data standard and that its data assets are in line with the defined data architecture and/or with the goals of the business.

　　Maintains the metadata registry, oversees data management, and/or all data sources and more.

　　Provides a standard common business vocabulary, expresses strategic data requirements, outlines high level integrated designs to meet these requirements, and aligns with enterprise strategy and related business architecture.

　　Expected to set data architecture principles, create models of data that enable the implementation of the intended business architecture, create diagrams showing key data entities, and create an inventory of the data needed to implement the architecture vision

　　Support operational use of data for business process functions such as customer centricity, supply chain, product positioning, sales efficiency, and other domain centric functions

　　Document data inventory and data flow diagrams to determine what can be measured, when and how

　　Responsible for designing, creating, deploying and managing an organization's data architecture.

　　Define how the data will be stored, consumed, integrated and managed by different data entities and IT systems, as well as any applications using or processing that data in some way.

　　Ensures that an organization follows a formal data standard and that its data assets are in line with the defined data architecture and/or with the goals of the business.

　　Maintains the metadata registry, oversees data management, optimizes databases and/or all data sources and more.

　　Provides a standard common business vocabulary, expresses strategic data requirements, outlines high level integrated designs to meet these requirements, and aligns with enterprise strategy and related business architecture.

　　Expected to set data architecture principles, create models of data that enable the implementation of the intended business architecture, create diagrams showing key data entities, and create an inventory of the data needed to implement the architecture vision

　　Support operational use of data for business process functions such as customer centricity, supply chain, product positioning, sales efficiency, and other domain centric functions

　　Document data inventory and data flow diagrams to determine what can be measured, when and how

　　Scope:

　　Understand the current data "state of affairs": A key objective of data architecture is to help the enterprise understand what data assets it owns, where they come from, where they reside, how they are used and what their levels of data quality are.

　　Reduce data redundancy and fragmentation: Although some data redundancy and fragmentation is inevitable, it must not be allowed to proliferate.

　　Eliminate unnecessary movement of data: Although reduced data fragmentation will lessen the need to move data, without oversight and management focus, there is a tendency for each new interface requirement to be addressed separately.

　　Develop integrative views of data: Because it is difficult, if not impossible, to eliminate all data fragmentation and redundancy, there will always be a requirement for integrated views of data to support a range of business and technical needs.

　　Reduce the number of technologies deployed: With fewer products to support, the range of skills required is smaller. It also allows staff to focus more on the nominated products, which enables them to deepen their skills and become more effective.

　　Improve data quality: Most enterprises are severely hampered in their efforts to perform integration and fully leverage their data because of poor data quality. A focus on data quality improvement is a critical component of the enterprise data architecture.

　　Improve security: Like quality, fragmented sources of data make security much more difficult to enforce. Not only must security measures be established for each data source, they must be coordinated, because inconsistent security measures may enable inappropriate access or prevent appropriate access.

　　Mapping data sources: An understanding of where data is stored and maintained is essential to data architecture. The data map should include descriptions of the business meaning of the data, its uses, its quality, the applications that maintain it and the database technology in which it is stored.

　　Documenting interfaces and data movement : Having mapped its sources, the next step in understanding enterprise data is to record how it is moved around the "virtual" enterprise. This includes the frequency of movement, the source and destination of each step, how the data is transformed as it moves, and any aggregation or calculations.

　　Defining technical standards and guidelines: Data architecture standards and guidelines should cover when and how to use the architected data. The guidelines should encourage reuse of existing data stores, as well as address issues of security, timeliness and quality.

　　Designing canonical data views: Because the format and the semantics of data differ from application to application, data must be transformed as it moves from its source to its destination. Without a canonical view of data, each interface will perform a unique point-to-point transformation, with the number of these transformations proliferating exponentially and becoming an enormous burden. A shared, canonical view makes these transformations more manageable

　　Defining technical standards and guidelines: Data architecture standards and guidelines should cover when and how to use the architected data. ), The technologies to be used for various purposes (for example, when to use extraction, transformation and loading tools, or an integration broker), and models of selected entities, objects and processes.

　　To succeed in this role requires a capacity for complexity and temperament that includes:

　　A very mature individual with the right balance of confidence and humility

　　Exceptional ability to absorb and handle high growth environment

　　Process oriented while also strongly developing and relying on interpersonal relationships across the company

　　Ability to connect equally well upwards, downwards and sideways in the organization

　　Self-motivated and driven towards excellence

　　A high level of EQ to be able to manage across a large team with significant diversity

　　Analyzing, processing and decision-making based on multidisciplinary and multi-functional data sources that could frequently be incomplete.

　　Ability to distinguish between and prioritizing urgent and important issues

　　Situational awareness and complex decision-making ability appropriate for the situation

　　Qualifications

　　Education:

　　Bachelor's Degree

　　Skills:

　　Certifications:

　　Languages:

　　Years of Experience:

　　10 - 15 Years

　　Work Experience:

　　Additional Information

　　Time Type:

　　Full time

　　Employee Type:

　　Assignee / Regular

　　Travel:

　　Yes, 25% of the Time

　　Relocation Eligible:

　　Yes

　　U.S. Salary Range:

　　$216,000.00 - $297,000.00

　　The salary offered to a selected candidate will be based on multiple factors including location, hire grade, job-related knowledge, skills, experience, and with consideration of internal equity of our current team members. In addition to a comprehensive benefits package, candidates may be eligible for other forms of compensation such as participation in a bonus and a stock award program, as applicable.

　　For all sales roles, the posted salary range is the Target Total Cash (TTC) range for the role, which is the sum of base salary and target bonus amount at 100% goal achievement.

　　Applied Materials is an Equal Opportunity Employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, national origin, citizenship, ancestry, religion, creed, sex, sexual orientation, gender identity, age, disability, veteran or military status, or any other basis prohibited by law.