- Oil & Gas, refining industry preferred.
- Artificial Intelligence (AI) and Machine Learning (ML) - Understanding of AI/ML concepts, algorithms, and platforms to design architectures that support intelligent systems and enable AI-driven applications -
- Proficient in Enterprise Architecture concepts and industry standard frameworks such as TOGAF, Zachman, BIZBOK, Lean Six Sigma, Agile (SAFe), etc.
- Experienced in defining and implementing EA standards (principles, templates) and processes (governance, content management)
- Define EA operating model, scope and implementation plan
- Define and implement Architecture Governance and Metrics management
- Define and implement EA Content Management processes
- Collaborate with various business and technology stakeholders to articulate architecture requirements/ use cases and translate into EA solutions
- Experienced in developing EA solution assets pertaining to current state analysis, transformation, rationalization, portfolio management, product evaluation, tech debt assessment etc,.
- Monitor industry trends and emerging technologies to identify opportunities for architectural innovation
- Experienced in identification of disruptive forces and investment guidance.
- Experienced in EA tools usage such as Lean IX, Alfabet, Ardoq, iServer
- Experienced in EA/ BPM modelling notations such as Archimate, BPMN 2.0, EPC
- Develop and deliver training content related to EA concepts, standards and processes
- Experienced in building and designing enterprise solution strategies and roadmaps and supporting their execution by working with highly skilled and diverse integrated project teams
- Preferred previous consulting experience in a large digital transformation for the refining industry
- Experience in ETRM is a plus.
- Demonstrated architecture leadership in the commercial and marketing domain.
- 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) and Machine Learning (ML) - Understanding of AI/ML concepts, algorithms, and platforms to design architectures that support intelligent systems and enable AI-driven applications.
- Business Acumen for Architecture - Understanding of business processes, strategies, and goals to align architectural decisions with organizational objectives.
- Cloud Computing - Knowing how to manage cloud services, develop cloud applications, and use cloud architecture to meet customer needs.
- Communication & Collaboration – Excellent communication skills to effectively interact with stakeholders, gather requirements, present architectural proposals, and collaborate with cross-functional teams.
- 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.
- Data Modeling – Skill in designing and implementing data models that align with business requirements, ensuring data integrity, performance, and scalability.
- Problem-Solving and Analytical Thinking - Strong problem-solving skills to identify architectural challenges, analyze requirements, evaluate options, and propose effective solutions.
- Systems Thinking - The ability to analyze complex systems and understand their interdependencies, considering both technical and business aspects, to develop comprehensive and scalable architectures.
- Technical Expertise - A strong understanding of various technologies, platforms, and systems relevant to the organization's architecture, such as networking, databases, cloud computing, and security.
- Bachelor's Degree in Information Technology, related field, or equivalent experience.
- 7+ years of relevant architecture experience required.
- Experience in hydrocarbon supply chain & marketing domains within a refining industry required.
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