Senior Director, IT Business Application

Who we are

Together, we’re on a mission to make good health more affordable and accessible, to help millions around the world enjoy healthier lives. It’s a mission that bonds our people across nearly 60 countries and a rich, diverse variety of nationalities and backgrounds. Working here means working with the world’s leading manufacturer of generic medicines, and the proud producer of many of the products on the World Health Organization’s Essential Medicines List. Today, at least 200 million people around the world take one of our medicines every single day. An amazing number, but we’re always looking for new ways to continue making a difference, and new people to make a difference with.

The opportunity

We are seeking a visionary and technically skilled Senior Director to lead our Data Platform & Strategy team, with a strong focus on enabling AI/ML capabilities across the enterprise. This role will drive the development of scalable data and AI, BI and agentic products, ensure platform reliability, and manage global teams and vendors. The ideal candidate will bring deep expertise in cloud-native data platforms, AI/ML operations, and modern data governance tools, with a strategic mindset and hands-on leadership experience.

How you’ll spend your day

Key Responsibilities:
Strategy & Leadership
•    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.

Platform & AI Enablement
•    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 (e.g., FAISS, Weaviate).

ML Ops & Site Reliability
•    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.

Data Product Development
•    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.

Governance & Tooling
•    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.

Global Team & Vendor Management
•    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.

Your experience and qualifications

Any equivalent combination of education, training, and/or experience that fulfills the requirements of the position will be considered.

•    Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field.
•    7+ years of experience in data platform engineering, architecture, or strategy roles.
•    Proven experience with:
o    Azure Databricks, SAP BW, SAP Datasphere
o    Informatica Cloud, Collibra,  SQL, Python
o    ML Ops tools (e.g., MLflow, Kubeflow, Azure ML)
o    LLM/agent frameworks (e.g., LangChain, Hugging Face, Azure OpenAI)
o    Vector databases (e.g., FAISS, Pinecone, Weaviate)
•    Strong understanding of agile methodologies and experience leading agile teams.
•    Experience in developing and supporting AI/ML products in a regulated industry.
•    Familiarity with SRE principles and cloud-native infrastructure automation.
•    Excellent stakeholder management and communication skills.
•    Experience managing global teams and external vendors.

Preferred Experience:
•    Pharmaceutical,  life sciences of finance industry experience.
•    Familiarity with data mesh principles and federated governance.
•    Knowledge of data privacy regulations (e.g., GDPR, HIPAA).
•    Experience with visualization tools (Power BI, Tableau) and project management tools (JIRA, Confluence).

Compensation Data

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