Senior Director, IT Business Application
Scorpion Therapeutics, Parsippany, New Jersey, United States
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
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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
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