Head of R&D Data Engineering

at  Sanofi

ABOUT SANOFI:

We are an innovative global healthcare company, driven by one purpose: we chase the miracles of science to improve people’s lives. Our team, across some 100 countries, is dedicated to transforming the practice of medicine by working to turn the impossible into the possible. We provide potentially life-changing treatment options and life-saving vaccine protection to millions of people globally, while putting sustainability and social responsibility at the center of our ambitions.
Sanofi has recently embarked into a vast and ambitious digital transformation program. A cornerstone of this roadmap is the acceleration of its data organization and adoption of artificial intelligence (AI) and machine learning (ML) solutions, to accelerate R&D, manufacturing and commercial performance and bring better drugs and vaccines to patients faster, to improve health and save lives.

KEY REQUIREMENTS:

• BS in computer science, software engineering or related area with at least 10+ years of experience in working on the development of data pipelines and data products.
• Demonstrated ability to lead a team of data engineers in product based operating model in collaboration with digital product owners to plan and execute large scale data projects, with proficiency in data modeling.
• Demonstrated knowledge of data consumption patterns, with a focus on Business Intelligence/Machine Learning/similar methods that rely on well-organized data.
• Understanding of software development metholody lifecycle practices and documentation including GxP compliance policies and procedures.
• Experience developing deployable code and data products and with deploying these under an agile work environment.
• Comfortable working in cloud and high-performance computing environments (e.g. AWS, GCP, Databricks, Apache Spark, Snowflake?).
• Demonstrated ability to work with leading data and database vendors with experience in determining optimal mix of what solutions to build, buy/configure.
• Excellent written and verbal communication, business analysis, data visualization and data storytelling skills.
• Strong interest in the use of data in the life and medical sciences to improve patient lives.
• Advanced degree (MS in computer science, engineering or a related technical discipline) with strong coding skills preferred.
• Experience in leading a team focused on the organization, storage, retrieval and initial processing of high throughput large biological and clinical data.
• Expertise with core data science languages (such as Python, R, Scala), and proficiency with key database systems (e.g. SQL, NoSQL).
• Familiarity with Omics data formats, digital pathology standards, Clinical/ Regulatory/ Safety Data and imaging data is advantageous.
• Knowledge of bioinformatics tools and pipelines is advantageous.
  The Fine Print:

• Lead a team of data and software engineers to plan, design, execute and continuously improve Sanofi’s ambitions in R&D data products.
• Keep pace with industry trends and pioneer new approaches within the data engineering space.
• Collaborate with scientific and business and information technology leadership to influence the Data strategy and direction. Present technical concepts to non-technical stakeholders.
• Strategically plan and execute data engineering initiatives, including the development of data pipelines. Design a comprehensive data engineering roadmap and execute the vision behind it.
• Lead technology execution of data engineering required to transform, harmonize data required for AI/analytics and build-out of re-useable aggregated data sets and APIs. Leverage knowledge of data architecture to enhance data pipeline effectiveness.
• Play a pivotal role in defining data engineering standards, driving innovation, and ensuring consistency across projects, adopting a Center of Excellence style approach.
• Build and manage talent of a team of engineers across multiple geographies to apply to data product teams including establishing a scalable approach to manage scale flexibly across internal resources, technology hubs and external service providers
• Oversee the movement of large data volumes into the organization’s data platform.
• Develop new techniques and pipelines to extract valuable insights from data.
• Empower data scientists and researchers with efficient access to high-quality data. Integrate multi-modal data sources (genomics, proteomics, imaging) into cohesive pipelines.
• Address challenges related to data harmonization, normalization, and feature extraction. Adhere to regulatory guidelines (e.g., HIPAA, GxP, GDPR) in handling sensitive data and implement robust data security measures.
• Contribute to evolving an agile, product-based delivery model in conjunction with product line leaders and product owners to manage and prioritize product strategy and backlog of individual products and solutions focused on delivering business outcomes
• Partner with Architecture CoE to enhance and ensure alignment with enterprise technology standards
• Build networks of key stakeholders across architecture CoE, data scientists, digital product leads, enterprise technology platform teams and PMO leaders. Foster a culture of continuous learning and development.
• Select the optimal approaches among the different vendors for the different data types and work closely with them to customize their offering for our needs.