Enterprise Data & AI Solutions Architect

We need to output HTML fragment with sections only if content present. Must not repeat job title. Must not include Job ID etc. Remove boilerplate, navigation, EEO, etc. Must preserve substantive info. We need to parse the posting. Key sections: - About the role? There's a paragraph: "Shape the Future with Us. At Lubrizol, we’re bringing to life the chemistry..." That's company description. Could be "About the role" or maybe "About the company". The instruction says use headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We need to decide which sections to include based on content. We have: - How You’ll Make An Impact (list of duties). That's responsibilities. - Required Qualifications That Enable Your Success (list). That's qualifications. - Preferred Qualifications That Drive You Forward (list). Could be also qualifications or skills. - Your Work Environment (description). Could be maybe "Work Environment" but not in allowed headings; we could maybe put under "About the role" or maybe not include if not matching allowed headings. The instruction: Use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It says e.g., meaning those are examples, but we should prefer those headings. Likely we should stick to those headings. So we need to map content to those headings. We have: - About the role: could include the introductory paragraph about Lubrizol and the role impact? Possibly. - Responsibilities: the bullet list under "How You’ll Make An Impact". - Qualifications: combine Required and Preferred? Could separate into Required Qualifications and Preferred Qualifications but heading only Qualifications. Could include both under Qualifications. - Skills: maybe we could extract skills from qualifications? But we could also have a Skills section if we have explicit skills list. Not present. - Benefits: we have a Benefits section with bullet list. - Pay: not specified (only "Competitive salary with performance-based bonus plans" but no specific number). The instruction: never create Pay/Schedule/Benefits sections unless the posting actually states them. Benefits we have explicit list, so we can include Benefits. Pay: we have "Competitive salary with performance-based bonus plans" which is a statement about pay but not specific numbers. Is that enough to create a Pay section? The instruction says never create Pay/Schedule/Benefits sections unless the posting actually states them. It does state "Competitive salary with performance-based bonus plans". That is a statement about pay, albeit vague. Should we include Pay? The instruction also says: Prefer a few substantive sections over many thin ones. And "never emit a heading followed by filler/placeholder text (e.g. "commensurate with experience", "not specified", "N/A", "varies", "TBD")". "Competitive salary with performance-based bonus plans" is not exactly filler; it's a statement but still vague. Might be considered placeholder? It's not a specific number or range. I'd lean to not include Pay section because it's not specific. Safer to omit Pay. - Schedule: we have "Full-time, Hybrid- Collaborate in office 4 days each week, with 1 flexible day". That's schedule info. So we can include Schedule section. Thus sections: About the role, Responsibilities, Qualifications, Benefits, Schedule. We need to ensure we don't repeat job title. Use

for each heading. We need to use

• for any list of duties/requirements/benefits. For prose use

  . We must preserve ALL substantive information; do not invent or summarize away detail. We need to extract the content. Let's gather: About the role: The introductory paragraphs before "How You’ll Make An Impact". It includes: "Shape the Future with Us. At Lubrizol, we’re bringing to life the chemistry behind clean water, efficient transportation, reliable infrastructure, critical medicines, and the products people rely on every day through science, sustainability, and a culture of inclusion. As part of our global team, you’ll be empowered to make a real impact - on your career, your community, and the world around you." Then also maybe the sentence: "As an Enterprise Data & AI Solutions Architect supporting our Data Intelligence team, you'll be at the forefront of our innovation, driving enterprise data architecture, analytics, integration, and AI-enabled initiatives that strengthen business performance across the organization. You'll collaborate with a diverse group of passionate individuals to deliver sustainable solutions to advance mobility, improve wellbeing, and enhance modern life." That is part of role description. So combine into About the role. We should not include duplicated lines. Responsibilities: The bullet list under "How You’ll Make An Impact". Let's extract each bullet: - Collaborate with business stakeholders to translate business requirements into scalable technical solutions aligned with enterprise data strategy and architecture. - Design and develop end-to-end, business process-driven solutions with a strong focus on data movement, analytics, and systems integration. - Lead solution design sessions and review technical specifications to ensure alignment with business requirements, architectural principles, and reliable data-by-design practices. - Guide the evaluation, selection, and implementation of tools supporting analytics, artificial intelligence, data governance, and data modeling. - Enforce data governance, data quality, and security practices across structured and unstructured data assets. - Provide architectural leadership for data platforms, extract-transform-load (ETL) and extract-load-transform (ELT) processes, data warehouses, data lakes, and analytics capabilities. - Assess emerging Microsoft, SAP, and cloud-native technologies, conduct proof-of-concepts, and recommend solutions that enhance enterprise data capabilities. - Review existing solutions and identify opportunities for continuous improvement, scalability, optimization, and integration. - Enable analytics, reporting, artificial intelligence and machine learning, business intelligence, and advanced data ingestion initiatives through modern data platforms. - Co-develop long-term technology strategies and innovation roadmaps across analytics, data engineering, and enterprise data platforms. That's 10 bullets. Qualifications: Combine Required and Preferred. Required Qualifications list: - Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering, or a related field. - 10+ years of experience in data architecture, data engineering, or enterprise architecture roles. - Proven experience as a Solutions Architect or similar role focused on end-to-end technical solutions and systems integration. - Strong understanding of solution architecture principles, methodologies, and best practices. - Experience in manufacturing, research and development (R&D), and/or process manufacturing environments. - Expertise with Microsoft data technologies including Azure Synapse, Azure Data Factory, AI Foundry, Microsoft Fabric, and Power BI. - Experience with cloud-based data platforms, preferably Microsoft Azure. - Experience with data lakehouse architectures and modern enterprise data platforms. - Familiarity with data governance frameworks, metadata management, and master data management (MDM). - Strong analytical, communication, stakeholder management, and cross-functional leadership skills. Preferred Qualifications list: - Understanding of artificial intelligence and machine learning data requirements and supporting infrastructure. - Knowledge of data security, regulatory compliance, and privacy frameworks such as General Data Protection Regulation (GDPR) and Health Insurance Portability and Accountability Act (HIPAA). - Hands-on experience with SAP ecosystems including SAP S/4HANA, SAP Datasphere, SAP Business Warehouse (BW), SAP Data Services, and SAP integration with Microsoft platforms. - Experience creating data modeling solutions leveraging SAP and Microsoft Azure data services, Microsoft Fabric, and Power BI. - Knowledge of conceptual, logical, and physical data modeling and database design. - TOGAF, DAMA, or related enterprise architecture or data management certifications. We should include both under Qualifications heading. Could separate into Required and Preferred subheadings? Not allowed; only use the allowed headings. Could just list all qualifications as a single list. That's fine. Benefits: list: - Competitive salary with performance-based bonus plans - 401(k) match + Age-Weighted Defined Contribution - Comprehensive medical, dental & vision coverage - Health Savings Account (HSA) - Paid holidays, vacation, and parental leave - Flexible work environment - Learning and development opportunities - Career and professional growth - Inclusive culture and vibrant community engagement - Learn more at https://benefits.lubrizol.com/ (maybe include as link? The instruction: preserve ALL substantive information; we can include the URL as part of the benefit item. Should we keep as plain text? Probably keep as is. Schedule: "Full-time, Hybrid- Collaborate in office 4 days each week, with 1 flexible day". Also maybe location? Location is Wickliffe, OH. But location is not schedule. Could we include location under About the role? Not needed. The instruction: do not put Job ID / requisition numbers as headings — fold minor metadata into a short

  or drop it. Location is minor metadata; we could include a short paragraph under About the role or maybe separate? But we have no heading for location. Could add a

  after the About the role paragraph: "Location: Wickliffe, OH, US, 44092-2298". However that is metadata; we could fold into a short

  . The instruction: "Do NOT repeat the job title as a heading (the page already shows it) and do NOT put Job ID / requisition numbers as headings — fold minor metadata into a short

  or drop it." So we can include location as a short

  maybe under About the role or as its own

  before sections. Probably better to include a short

  after the About the role heading? Actually About the role heading expects heading then content. We could put location as a

  after the About the role content but before next heading. That is okay. We must not include boilerplate like "Apply now » Start apply with LinkedIn Apply Now Please wait..." etc. Also remove duplicated lines, navigation, legal, EEO, etc. We need to output only HTML fragment. Let's craft:

  About the role

  Shape the Future with Us. At Lubrizol, we’re bringing to life the chemistry behind clean water, efficient transportation, reliable infrastructure, critical medicines, and the products people rely on every day through science, sustainability, and a culture of inclusion. As part of our global team, you’ll be empowered to make a real impact - on your career, your community, and the world around you. As an Enterprise Data & AI Solutions Architect supporting our Data Intelligence team, you'll be at the forefront of our innovation, driving enterprise data architecture, analytics, integration, and AI-enabled initiatives that strengthen business performance across the organization. You'll collaborate with a diverse group of passionate individuals to deliver sustainable solutions to advance mobility, improve wellbeing, and enhance modern life.

  Location: Wickliffe, OH, US, 44092-2298

  Responsibilities

  • Collaborate with business stakeholders to translate business requirements into scalable technical solutions aligned with enterprise data strategy and architecture.
  • Design and develop end-to-end, business process-driven solutions with a strong focus on data movement, analytics, and systems integration.
  • Lead solution design sessions and review technical specifications to ensure alignment with business requirements, architectural principles, and reliable data-by-design practices.
  • Guide the evaluation, selection, and implementation of tools supporting analytics, artificial intelligence, data governance, and data modeling.
  • Enforce data governance, data quality, and security practices across structured and unstructured data assets.
  • Provide architectural leadership for data platforms, extract-transform-load (ETL) and extract-load-transform (ELT) processes, data warehouses, data lakes, and analytics capabilities.
  • Assess emerging Microsoft, SAP, and cloud-native technologies, conduct proof-of-concepts, and recommend solutions that enhance enterprise data capabilities.
  • Review existing solutions and identify opportunities for continuous improvement, scalability, optimization, and integration.
  • Enable analytics, reporting, artificial intelligence and machine learning, business intelligence, and advanced data ingestion initiatives through modern