Director Platform/Enterprise Architect Data & AI

Job description

Join our Digital & Technology – Enterprise & Solution Architecture unit at Animal Nutrition & Health and help shape the future of data architecture across the enterprise. We are seeking a seasoned Enterprise Data Architect who will also serve as a Data Domain Architect, driving strategic data initiatives, governance, and innovation across our global data landscape.

This role will be instrumental in designing and evolving enterprise-wide data architecture, enabling advanced analytics, AI/ML capabilities, and ensuring data integrity, security, and compliance across platforms.

Role

Director Enterprise Architect Data & AI

Your key responsibilities:

• Enterprise Data Architecture Leadership: Define and evolve enterprise data architecture strategy, frameworks, standards, operating models, and ownership of data catalog, lineage, and metadata aligned with business and IT goals.
• Domain Data Architecture: Act as domain architect across key business areas, designing business-aligned data models, semantic layers, KPIs, and reusable data products while driving data maturity and MDM adoption.
• Data Platform & Integration: Architect scalable, resilient data platforms and ingestion pipelines (batch/streaming) using Kafka, Informatica, Databricks, APIs, and cloud-native services to meet SLAs for availability, quality, and performance.
• Governance, Security & DevOps: Establish data governance, security, and compliance standards; implement CI/CD, Infrastructure as Code, and DataOps practices to ensure quality, consistency, and secure delivery of data products.
• Cost Optimization & FinOps: Drive cloud FinOps best practices by designing cost-efficient data pipelines and platforms, monitoring usage, and optimizing resource consumption through serverless and reserved capacity models.
• Innovation & Stakeholder Enablement: Enable advanced analytics and AI/ML use cases, lead innovation pilots and PoCs, provide architectural oversight, and mentor teams while partnering closely with business and technology stakeholders.

You bring:

• Cloud Data Architecture & Mesh: Design and lead a decentralized Cloud Data Mesh on AWS, integrating legacy enterprise systems (e.g., SAP S/4HANA, BW/4HANA) with cloud-native data platforms such as Databricks and Informatica.
• Data Governance, Security & MDM: Implement robust governance, security, and metadata frameworks using Databricks Unity Catalog, AWS IAM, and Informatica MDM to enable access control, privacy, lineage, discovery, and trusted master data.
• End-to-End Data Lifecycle Expertise: Demonstrate deep expertise across the full data lifecycle—from ingestion (SAP ingestion tools, low-code/no-code), transformation (Spark), to consumption via APIs and analytics platforms.
• Integration, Streaming & Platforms: Architect scalable batch and streaming data pipelines and enterprise integration patterns for complex ecosystems including SAP, CRM platforms, and modern data platforms (Databricks, Informatica; Palantir preferred).
• DataOps, DevOps & Cloud Enablement: Drive architectural adoption through DataOps practices, CI/CD pipelines, Infrastructure-as-Code (Terraform), and cloud-native DevOps to ensure automation, scalability, and agility on AWS.
• Leadership & Experience: Bring 17+ years of enterprise data architecture and domain modeling experience, strong stakeholder leadership and communication skills, and a Bachelor’s/Master’s degree in Computer Science, Data Engineering, or a related field.

We bring:

• Lead enterprise-wide data transformation initiatives to modernize and optimize data strategy and operations.
• Drive adoption of data-driven decision-making and influence strategic business and IT initiatives.
• Promote data innovation by identifying and implementing emerging technologies and advanced analytics solutions.
• Collaborate with global teams to design scalable, high-performance data platforms and architectures.
• Establish best practices for data governance, quality, and integration across the enterprise.
• Mentor and enable teams, fostering a culture of continuous improvement and data excellence.