Senior Director, IT Business Application

Role Summary

Lead the Data Platform & Strategy team with a focus on enabling AI/ML capabilities across the enterprise. Drive scalable data and AI, BI, and agentic products, ensure platform reliability, and manage global teams and vendors. Seek cloud-native data platforms, AI/ML operations, and modern data governance tools with strategic, hands-on leadership.

Responsibilities

• Define and execute a comprehensive data and AI platform strategy aligned with enterprise goals.
• Drive adoption of modern data architectures (e.g., Data Mesh) and AI/ML product frameworks.
• Partner with business and technology leaders to prioritize and deliver high-impact data and AI initiatives.
• Lead the development and scaling of a cloud-native data platform (Azure, Databricks, Snowflake).
• Integrate SAP BW and SAP Datasphere into the broader data and AI ecosystem.
• Enable AI/ML product development by ensuring robust data pipelines, feature stores, and model registries.
• Support LLM-based applications and agentic workflows using technologies such as LangChain, Hugging Face, Azure OpenAI, and vector databases (FAISS, Weaviate).
• Establish and maintain ML Ops practices for model deployment, monitoring, and lifecycle management.
• Implement site reliability engineering (SRE) principles to ensure platform uptime, scalability, and performance.
• Collaborate with DevOps and cloud engineering teams to automate infrastructure and CI/CD pipelines.
• Lead agile teams in the design, development, and deployment of data and AI products.
• Translate business needs into scalable, governed, and reusable data assets.
• Ensure compliance with data privacy and regulatory standards.
• Implement data governance frameworks, including enterprise reporting using Informatica Cloud Data Manager and similar tools.
• Maintain centralized metadata, lineage, and cataloging for discoverability and trust.
• Manage and mentor a global team of data engineers, ML engineers, solution architects, and data analysts.
• Govern vendor relationships, performance metrics, and contract negotiations.
• Drive vendor selection and onboarding in collaboration with procurement and legal.

Qualifications

• Required: 7+ years of experience in data platform engineering, architecture, or strategy roles.
• Required: Proven experience with: Azure Databricks, SAP BW, SAP Datasphere; Informatica Cloud, Collibra, SQL, Python; ML Ops tools (e.g., MLflow, Kubeflow, Azure ML); LLM/agent frameworks (e.g., LangChain, Hugging Face, Azure OpenAI); Vector databases (e.g., FAISS, Pinecone, Weaviate).
• Required: Strong understanding of agile methodologies and experience leading agile teams.
• Required: Experience in developing and supporting AI/ML products in a regulated industry.
• Required: Familiarity with SRE principles and cloud-native infrastructure automation.
• Required: Excellent stakeholder management and communication skills.
• Required: Experience managing global teams and external vendors.
• Preferred: Pharmaceutical, life sciences or finance industry experience.
• Preferred: Familiarity with data mesh principles and federated governance.
• Preferred: Knowledge of data privacy regulations (e.g., GDPR, HIPAA).
• Preferred: Experience with visualization tools (Power BI, Tableau) and project management tools (JIRA, Confluence).

Education

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field.

Skills

• Cloud-native data platforms (Azure Databricks, Snowflake)
• Data governance, metadata, lineage, cataloging
• ML Ops and model lifecycle management
• LLM/agent frameworks and vector databases
• Data privacy and regulatory compliance
• Agile leadership and global team management
• Vendor management and contract negotiation