Key Responsibilities:

• Solution Design: Architect and design data solutions using tools like AWS, Snowflake, and Databricks.
• Project Management: Oversee the delivery of data lake projects, including data acquisition, quality, transformation, and publishing.
• Collaboration: Work closely with business stakeholders to understand requirements and deliver solutions that meet their needs.
• Innovation: Stay updated with industry trends and emerging technologies to drive continuous improvement.
• Emerging Technology Monitoring, Consulting, Influencing & persuading, Unbossed Leadership, IT governance, building High Performing Teams, Vendor Management, Innovative & Analytical Technologies.
• Leveraging Technology for business and customer needs.
• Solid understanding of Analytical and technical frameworks for descriptive and prescriptive analytics.
• Awareness of integration patterns across MDM/RDM and transactional systems.
• Production experience delivering data lake projects, including data acquisition, quality, transformation, and publishing.
• Strong exposure to data security and governance policy definitions and enforcement capabilities.
• Data product-centric approach to defining solutions. Collaborate with business in gathering requirements, grooming product backlogs, driving delivery, and ongoing data product enhancements.
• Agile delivery experience managing multiple concurrent delivery cycles.
• Sound foundation in Analytical Data life cycle management.
• Awareness of Data product change Management and risk mitigation.

Key Performance Indicators:

• Achieved targets in Enterprise business case contribution, KPIs, customer satisfaction, and innovation measures 
• Business capability, vision & strategy clearly defined, communicated, and executed, well aligned to business strategy and Enterprise IT strategy, and providing a competitive advantage to Novartis
• Role model with the highest standards of professional conduct in leading the business capability area in line with the new IT operating model
• Deployment of digital platforms and services at scale to deliver the digital strategy
• Operational Efficiency
  • Data Processing Time: Average time taken to process and make data available for analysis.
  • System Uptime: Percentage of time the data systems are operational and available.
• Stakeholder Satisfaction:
  • Stakeholder Feedback Score: Ratings from internal stakeholders on the usefulness and accessibility of data.
  • Issue Resolution Time: Average time taken to resolve data-related issues reported by stakeholders.
• Innovation and Improvement:
  • Implementation of New Technologies: Number of new data tools or technologies successfully integrated.
  • Process Improvement Initiatives: Number of initiatives aimed at improving data architecture processes.
• Project Delivery:
  • On-time Delivery Rate: Percentage of projects completed on or before the deadline.
  • Project Success Rate: Percentage of projects that meet their objectives and deliver expected outcomes.
• Data Utilization:
  • Data Usage Rate: Frequency and extent to which data is accessed and used by the commercial team.
  • Insights Generated: Number of actionable insights derived from data analytics.

Skills:

• Emerging Technology Monitoring, Consulting, Influencing & persuading, Unbossed Leadership, IT governance, building High Performing Teams, Vendor Management, Innovative & Analytical Technologies.
• 10+ Yrs of Solid understanding of Analytical and technical frameworks for descriptive and prescriptive analytics.
• Strong familiarity with AWS, Databricks, and Snowflake service offerings.
• Experience integrating disparate analytical and visualization platforms.
• Strong knowledge of MLOps and project life cycle management.
• Strong exposure to data security and governance policy definitions and enforcement capabilities.
• Data product-centric approach to defining solutions. Collaborate with business in gathering requirements, grooming product backlogs, driving delivery, and ongoing data product enhancements
• Agile delivery experience managing multiple concurrent delivery cycles.
• Sound foundation in Analytical Data life cycle management.
• Awareness of Data product change Management and risk mitigation.
• Strong analytical and problem-solving skills, effective communication, and the ability to influence and collaborate with cross-functional teams

Education: 

• Bachelor’s degree in computer science, engineering, or a related field.

Desirable:

Experience with pharmaceutical data and familiarity with global data sources

Commitment to Diversity & Inclusion:

We are committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve.

Accessibility and accommodation

Novartis is committed to working with and providing reasonable accommodation to individuals with disabilities.

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