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 transformation and of the adoption of artificial intelligence (AI) and machine learning (ML) solutions that will accelerate Manufacturing and supply performance and help bring drugs and vaccines to patients faster, to improve health and save lives.
As part of the Digital M&S Foundations organization, the data modeler designs implements, and documents data architecture and data modeling solutions, which include the use of relational and dimensional databases. These solutions support Manufacturing and Supply Data Analytical products and other business interests.
The successful candidate will:
Be responsible for the development of the conceptual, logical, and physical data models in line with the architecture and platform strategy
Oversee and govern the expansion of existing data architecture and the optimization of data query performance via best practices. The candidate must be able to work independently and collaboratively with the M&S teams
Demonstrate strong expertise in one of the following functional business areas of M&S: Manufacturing, Quality, or Supply Chain
Roles & Responsibilities
Design and implement business data models in line with data foundation strategy and standards
Work with business and application/solution teams to understand requirements, build data flows, and develop conceptual/logical/physical data models
Define and govern data modeling and design standards, tools, best practices, and related development for enterprise data models.
Identify the architecture, infrastructure, and interfaces to data sources, tools supporting automated data loads, security concerns, and analytic models.
Hands-on data modeling, design, configuration, and performance tuning
Work proactively and independently to address project requirements and articulate issues/challenges to reduce project delivery risks.
Bachelor’s or master’s degree in computer/data engineering technical or related experience.
5+ years of hands-on relational, dimensional, and/or analytic experience, including 5+ years of hands-on experience with data from core manufacturing and supply chain systems such as SAP, Quality Management, LIMS, MES, Planning
Experience hands-on programming in SQL
Experience with data warehouse (Snowflake), data lake (AWS-based), and enterprise big data platforms in a pharmaceutical company.
Good knowledge of metadata management, data modeling, and related tools: Snowflake, Informatica, DBT
Experience with Agile
Good communication, and presentation skills
Pursue progress, discover extraordinary
Better is out there. Better medications, better outcomes, better science. But progress doesn’t happen without people – people from different backgrounds, in different locations, doing different roles, all united by one thing: a desire to make miracles happen. So, let’s be those people.
At Sanofi, we provide equal opportunities to all regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, or gender identity.
At Sanofi diversity and inclusion is foundational to how we operate and embedded in our Core Values. We recognize to truly tap into the richness diversity brings we must lead with inclusion and have a workplace where those differences can thrive and be leveraged to empower the lives of our colleagues, patients and customers. We respect and celebrate the diversity of our people, their backgrounds and experiences and provide equal opportunity for all.