Enterprise Engagement Architect | Security

About the Role

The Enterprise Architect (EA) for Cybersecurity and Infrastructure will understand enterprise environments through the relationships between people, process and the technologies that enable them. Through this understanding, the EA will support the creation of current and future state plans that align with MPC strategic priorities. The EA will be responsible for standards and architecture governance while also supporting the research and development of initiatives to introduce changes in architecture. The EA will influence digital transformation roadmaps by leading the strategy and approach for how we manage and govern our enterprise architecture practice for the Corporate and Performance Excellence domains. The EA will partner closely with other architects and technology leaders to understand and improve how we align with enterprise MPC strategic priorities to Cybersecurity and Infrastructure priorities. The EA will help us understand the state of our enterprise architecture through data in the architecture repository and champion data driven decisions that advance our digital strategy. This position belongs to a family of jobs with increasing responsibility, competency, and skill level. Actual position title and pay grade will be based on the selected candidate’s experience and qualifications.

Responsibilities 

• Leads the development and implementation of enterprise architecture standards and guidelines. Participates in and leads architecture reviews and ensures architecture adherence.
• Collaborates with executive management to influence and shape strategic initiatives. Defines and drives the enterprise architecture vision, strategy, and roadmap. Leads the identification of disruptive forces and investment guidance.
• Conducts trend analysis and provides strategic direction.
• Provides a framework for architectural decision-making, including assessment of technology options. Assesses and mitigates risks associated with enterprise architecture decisions. Leading the resolution of complex architectural challenges and conflicts. Oversees innovation tracking and management.
• Monitors industry trends and emerging technologies to identify opportunities for architectural innovation. Guides the analysis of business and operating models.
• Takes charge of constructing future-state business models. Drives analysis of future-state capabilities and organizational requirements.• Integrates emerging technologies effectively. Develops and manages implementation plans for the portfolio.
• Guides and mentors other architects and teams on enterprise architecture principles and practices. Leads collaboration with business architects and leaders.
• Ensures alignment and coordination of architecture activities. Presents comprehensive IT investment roadmaps and gap analyses.

Education and Experience

• Bachelor’s Degree in Information Technology, related field, or equivalent experience.
• 7+ years of relevant architecture experience required.
• Experience with building and designing enterprise solution strategies and roadmap and supporting their execution by working with highly skilled and diverse integrated project teams preferred.
• Demonstrated ability to quickly understand new technologies and concepts.
• Experience working within an organization with common IT practices, frameworks, and tools for TOGAF, ITSM, ITIL, COBIT, ISO, NIST, Lean Six Sigma, Agile (SAFe), etc.
• Certified Information Systems Security Professional (CISSP) preferred.
• Experience with Zero Trust Strategy a plus.
• Experience in Operational Technology a plus.

Skills

• Analytical Thinking - Strong problem-solving skills to identify architectural challenges, analyze requirements, evaluate options, and propose effective solutions.
• Architecture Frameworks - Proficiency in widely used architecture frameworks like TOGAF (The Open Group Architecture Framework) or Zachman Framework to structure and organize architectural artifacts and processes.
• Artificial Intelligence (AI) - Artificial Intelligence (AI) refers to the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions), and self-correction. AI encompasses a broad range of techniques and approaches,including machine learning, neural networks, natural language processing, computer vision, robotics, and expert systems, among others. The ultimate goal of AI is to create machines that can perform tasks that typically require human intelligence, such as understanding natural language, recognizing patterns, making decisions, and solving problems.
• Authentic Communicator - Expresses ideas and information, both verbally and in writing, clearly and credibly. Listens to understand and fosters constructive dialogue.
• Business Acumen - Applies knowledge of MPC’s business, industry and the marketplace to advance the organization’s goals. Makes decisions and recommendations clearly linked to MPC’s strategy.
• Cloud Computing - Knowing how to manage cloud services, develop cloud applications and use cloud architecture to meet customer needs.
• Continuous Improvement Mindset - Identifies and leads opportunities for continuous improvement and value creation, both incremental and large-scale.
• Data Modeling - Skill in designing and implementing data models that align with business requirements, ensuring data integrity, performance, and scalability.
• Digital Transformation - Digital Transformation is the adoption of digital technology to transform services or businesses, through replacing non-digital or manual processes with digital processes or replacing older digital technology with newer digital technology.
• Functional Expertise - A strong understanding of various technologies, platforms, and systems relevant to the organization's architecture, such as networking, databases, cloud computing, and security.
• Machine Learning - Machine learning is a branch of Artificial Intelligence (AI) and computer science that involves the development of algorithms and statistical models that enable computers to progressively improve their performance on a specific task through learning from data, without being explicitly programmed. In essence, machine learning algorithms learn from patterns and relationships in data to make predictions, decisions, or identify patterns, often with the goal of optimizing some objective function or improving performance over time.
• Process Orchestration - Process orchestration refers to the coordination and management of various tasks, activities, and resources within a workflow or business process. It involves organizing, sequencing, and automating individual tasks or sub-processes to ensure that the overall process operates smoothly and efficiently. Process orchestration typically involves integrating disparate systems, applications, and services to streamline operations and improve collaboration across different parts of an organization. It often employs workflow management tools, automation software, and integration platforms to facilitate communication, data exchange, and decision-making among different components of the process. The goal of process orchestration is to optimize the flow of work, minimize delays and bottlenecks, and enhance overall productivity and performance.
• Strategic Outlook - Examines issues, generates ideas, creates future scenarios and develops plans with a long-term perspective. Ensures short-term goals support long-term strategy and that organizational/functional strategy aligns with and supports MPC’s overall business strategy.
• Systems Thinking - The ability to analyze complex systems and understand their interdependencies, considering both technical and business aspects, to develop comprehensive and scalable architectures.