Data Solutions Architect (WW Operations Business Process Reengineering)
Apple
Data Solutions Architect (WW Operations Business Process Reengineering)
Job Description
Imagine what you could do here. At Apple, we believe new ideas have a way of becoming phenomenal products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. The people here at Apple don’t just create products — they create the kind of wonder that’s revolutionised entire industries. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple, and help us leave the world better than we found it. Apple Operations and Supply Chain delivers to customer promise with revolutionary precision, accuracy and at an immense scale. At the heart of that revolution precision, accuracy and scale are best in class processes and systems. We are seeking an experienced and hands-on Supply Chain Data Solutions Architect to lead the development and deployment of next-generation AI systems in our global supply chain function. This role will focus on implementing cutting-edge Generative AI and Agentic AI solutions, backed by strong Data Engineering practices and supply chain domain expertise. As a Data Solutions Architect, we look forward to your bridging the gap between AI capabilities and real-world business challenges, driving automation, resilience, and efficiency across the value chain. Key responsibilities include : AI & Agentic Systems Implementation : - Design, build, and deploy Generative AI and Agentic AI solutions tailored for supply chain use cases (e.g., demand forecasting, scenario planning, exception handling, data monitoring). - Leverage technologies like LLMs, autonomous agents, reinforcement learning, and reasoning frameworks to power decision-making tools. - Lead the experimentation and operationalization of AI agents across planning, sourcing, logistics, and fulfillment domains. Data Engineering & Infrastructure : - Architect scalable data pipelines that ingest, transform, and serve high-quality data for AI/ML workloads. - Ensure robust data integration from ERP, Supply Chain systems, and third-party APIs (e.g., weather, risk). - Implement MLOps best practices to manage AI lifecycle: versioning, monitoring, retraining, and governance. Supply Chain Domain Expertise : - Work closely with cross functional supply chain IT and operations teams to translate business challenges into AI-driven solutions. - Bring functional understanding across areas like S&OP, inventory management, supplier risk, and transportation optimization. - Drive continuous improvement through digital twin models, predictive analytics, and scenario simulation. Cross-Functional Leadership : - Collaborate with data scientists, and engineers in a fast-paced agile environment. - Act as a thought leader in identifying high-value opportunities for AI within the enterprise supply chain. - Present technical concepts and business value to executive stakeholders clearly and persuasively.
Locations
- Hyderabad, Telangana, India
Salary
Skills Required
- Supply Chain Data Solutions Architectintermediate
- Generative AI implementationintermediate
- Agentic AI implementationintermediate
- Data Engineeringintermediate
- LLMsintermediate
- Autonomous agentsintermediate
- Reinforcement learningintermediate
- Reasoning frameworksintermediate
- Demand forecastingintermediate
- Scenario planningintermediate
- Exception handlingintermediate
- Data monitoringintermediate
- Scalable data pipelinesintermediate
- Data integrationintermediate
- ERP systemsintermediate
- Supply Chain systemsintermediate
- Third-party APIsintermediate
- MLOps best practicesintermediate
- AI lifecycle managementintermediate
- Versioningintermediate
- Monitoringintermediate
- Retrainingintermediate
- Governanceintermediate
- S&OPintermediate
- Inventory managementintermediate
- Supplier riskintermediate
- Transportation optimizationintermediate
- Digital twin modelsintermediate
- Predictive analyticsintermediate
- Scenario simulationintermediate
- Cross-functional collaborationintermediate
- Agile environmentintermediate
- Thought leadershipintermediate
- Stakeholder presentationintermediate
- Supply chain domain expertiseintermediate
Required Qualifications
- Bachelor’s or Master’s in Computer Science, Data Science, Operations Research, or a related field. (degree in master)
- 10+ years of experience in data engineering, AI/ML, or analytics roles. (experience, 10 years)
- 4+ years of hands-on experience with Generative AI (e.g., GPT, Claude, open-source LLMs) and Agent-based architectures (LangChain, AutoGen, etc.). (experience, 4 years)
- Strong background in data engineering: SQL, Spark, Python, Airflow, cloud (AWS/GCP/Azure), and data lakes. (experience)
- Deep understanding of supply chain processes (planning, logistics, procurement, manufacturing). (experience)
- Familiarity with MLOps tools, vector databases (e.g., Pinecone, FAISS), and AI safety practices. (experience)
Preferred Qualifications
- Experience with commercial supply chain platforms (e.g., Kinaxis, Blue Yonder). (experience)
- Exposure to digital twin and simulation platforms. (experience)
- Strong storytelling, communication, and stakeholder management skills. (experience)
- Experience in building and leading cross-functional project teams in a matrixed organization. (experience)
Responsibilities
- As a Data Solutions Architect, we look forward to your bridging the gap between AI capabilities and real-world business challenges, driving automation, resilience, and efficiency across the value chain.
- Key responsibilities include :
- AI & Agentic Systems Implementation :
- - Design, build, and deploy Generative AI and Agentic AI solutions tailored for supply chain use cases (e.g., demand forecasting, scenario planning, exception handling, data monitoring).
- - Leverage technologies like LLMs, autonomous agents, reinforcement learning, and reasoning frameworks to power decision-making tools.
- - Lead the experimentation and operationalization of AI agents across planning, sourcing, logistics, and fulfillment domains.
- Data Engineering & Infrastructure :
- - Architect scalable data pipelines that ingest, transform, and serve high-quality data for AI/ML workloads.
- - Ensure robust data integration from ERP, Supply Chain systems, and third-party APIs (e.g., weather, risk).
- - Implement MLOps best practices to manage AI lifecycle: versioning, monitoring, retraining, and governance.
- Supply Chain Domain Expertise :
- - Work closely with cross functional supply chain IT and operations teams to translate business challenges into AI-driven solutions.
- - Bring functional understanding across areas like S&OP, inventory management, supplier risk, and transportation optimization.
- - Drive continuous improvement through digital twin models, predictive analytics, and scenario simulation.
- Cross-Functional Leadership :
- - Collaborate with data scientists, and engineers in a fast-paced agile environment.
- - Act as a thought leader in identifying high-value opportunities for AI within the enterprise supply chain.
- - Present technical concepts and business value to executive stakeholders clearly and persuasively.
Tags & Categories
Answer 10 quick questions to check your fit for Data Solutions Architect (WW Operations Business Process Reengineering) @ Apple.
10 Questions
~2 Minutes
Instant Score
Related Books and Jobs
Data Solutions Architect (WW Operations Business Process Reengineering)
Apple
Data Solutions Architect (WW Operations Business Process Reengineering)
Job Description
Imagine what you could do here. At Apple, we believe new ideas have a way of becoming phenomenal products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. The people here at Apple don’t just create products — they create the kind of wonder that’s revolutionised entire industries. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple, and help us leave the world better than we found it. Apple Operations and Supply Chain delivers to customer promise with revolutionary precision, accuracy and at an immense scale. At the heart of that revolution precision, accuracy and scale are best in class processes and systems. We are seeking an experienced and hands-on Supply Chain Data Solutions Architect to lead the development and deployment of next-generation AI systems in our global supply chain function. This role will focus on implementing cutting-edge Generative AI and Agentic AI solutions, backed by strong Data Engineering practices and supply chain domain expertise. As a Data Solutions Architect, we look forward to your bridging the gap between AI capabilities and real-world business challenges, driving automation, resilience, and efficiency across the value chain. Key responsibilities include : AI & Agentic Systems Implementation : - Design, build, and deploy Generative AI and Agentic AI solutions tailored for supply chain use cases (e.g., demand forecasting, scenario planning, exception handling, data monitoring). - Leverage technologies like LLMs, autonomous agents, reinforcement learning, and reasoning frameworks to power decision-making tools. - Lead the experimentation and operationalization of AI agents across planning, sourcing, logistics, and fulfillment domains. Data Engineering & Infrastructure : - Architect scalable data pipelines that ingest, transform, and serve high-quality data for AI/ML workloads. - Ensure robust data integration from ERP, Supply Chain systems, and third-party APIs (e.g., weather, risk). - Implement MLOps best practices to manage AI lifecycle: versioning, monitoring, retraining, and governance. Supply Chain Domain Expertise : - Work closely with cross functional supply chain IT and operations teams to translate business challenges into AI-driven solutions. - Bring functional understanding across areas like S&OP, inventory management, supplier risk, and transportation optimization. - Drive continuous improvement through digital twin models, predictive analytics, and scenario simulation. Cross-Functional Leadership : - Collaborate with data scientists, and engineers in a fast-paced agile environment. - Act as a thought leader in identifying high-value opportunities for AI within the enterprise supply chain. - Present technical concepts and business value to executive stakeholders clearly and persuasively.
Locations
- Hyderabad, Telangana, India
Salary
Skills Required
- Supply Chain Data Solutions Architectintermediate
- Generative AI implementationintermediate
- Agentic AI implementationintermediate
- Data Engineeringintermediate
- LLMsintermediate
- Autonomous agentsintermediate
- Reinforcement learningintermediate
- Reasoning frameworksintermediate
- Demand forecastingintermediate
- Scenario planningintermediate
- Exception handlingintermediate
- Data monitoringintermediate
- Scalable data pipelinesintermediate
- Data integrationintermediate
- ERP systemsintermediate
- Supply Chain systemsintermediate
- Third-party APIsintermediate
- MLOps best practicesintermediate
- AI lifecycle managementintermediate
- Versioningintermediate
- Monitoringintermediate
- Retrainingintermediate
- Governanceintermediate
- S&OPintermediate
- Inventory managementintermediate
- Supplier riskintermediate
- Transportation optimizationintermediate
- Digital twin modelsintermediate
- Predictive analyticsintermediate
- Scenario simulationintermediate
- Cross-functional collaborationintermediate
- Agile environmentintermediate
- Thought leadershipintermediate
- Stakeholder presentationintermediate
- Supply chain domain expertiseintermediate
Required Qualifications
- Bachelor’s or Master’s in Computer Science, Data Science, Operations Research, or a related field. (degree in master)
- 10+ years of experience in data engineering, AI/ML, or analytics roles. (experience, 10 years)
- 4+ years of hands-on experience with Generative AI (e.g., GPT, Claude, open-source LLMs) and Agent-based architectures (LangChain, AutoGen, etc.). (experience, 4 years)
- Strong background in data engineering: SQL, Spark, Python, Airflow, cloud (AWS/GCP/Azure), and data lakes. (experience)
- Deep understanding of supply chain processes (planning, logistics, procurement, manufacturing). (experience)
- Familiarity with MLOps tools, vector databases (e.g., Pinecone, FAISS), and AI safety practices. (experience)
Preferred Qualifications
- Experience with commercial supply chain platforms (e.g., Kinaxis, Blue Yonder). (experience)
- Exposure to digital twin and simulation platforms. (experience)
- Strong storytelling, communication, and stakeholder management skills. (experience)
- Experience in building and leading cross-functional project teams in a matrixed organization. (experience)
Responsibilities
- As a Data Solutions Architect, we look forward to your bridging the gap between AI capabilities and real-world business challenges, driving automation, resilience, and efficiency across the value chain.
- Key responsibilities include :
- AI & Agentic Systems Implementation :
- - Design, build, and deploy Generative AI and Agentic AI solutions tailored for supply chain use cases (e.g., demand forecasting, scenario planning, exception handling, data monitoring).
- - Leverage technologies like LLMs, autonomous agents, reinforcement learning, and reasoning frameworks to power decision-making tools.
- - Lead the experimentation and operationalization of AI agents across planning, sourcing, logistics, and fulfillment domains.
- Data Engineering & Infrastructure :
- - Architect scalable data pipelines that ingest, transform, and serve high-quality data for AI/ML workloads.
- - Ensure robust data integration from ERP, Supply Chain systems, and third-party APIs (e.g., weather, risk).
- - Implement MLOps best practices to manage AI lifecycle: versioning, monitoring, retraining, and governance.
- Supply Chain Domain Expertise :
- - Work closely with cross functional supply chain IT and operations teams to translate business challenges into AI-driven solutions.
- - Bring functional understanding across areas like S&OP, inventory management, supplier risk, and transportation optimization.
- - Drive continuous improvement through digital twin models, predictive analytics, and scenario simulation.
- Cross-Functional Leadership :
- - Collaborate with data scientists, and engineers in a fast-paced agile environment.
- - Act as a thought leader in identifying high-value opportunities for AI within the enterprise supply chain.
- - Present technical concepts and business value to executive stakeholders clearly and persuasively.
Tags & Categories
Answer 10 quick questions to check your fit for Data Solutions Architect (WW Operations Business Process Reengineering) @ Apple.
10 Questions
~2 Minutes
Instant Score
Related Books and Jobs