Data Engineering Expert-R&D Development

Job description

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 transformation and of the 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.

Our vision for digital, data analytics and AI

Join us on our journey in enabling Sanofi’s Digital Transformation through becoming an AI first organization. This means:

·  AI Factory - Versatile Teams Operating in Cross Functional Pods: Utilizing digital and data resources to develop AI products, bringing data management, AI and product development skills to products, programs and projects to create an agile, fulfilling and meaningful work environment.
·  Leading Edge Tech Stack: Experience build products that will be deployed globally on a leading-edge tech stack.
·  World Class Mentorship and Training: Working with renowned leaders and academics in machine learning to further develop your skillsets.

Job Highlights:

·  Establish technical designs to meet business and technical requirements as a prime data engineering lead
·  Write clean, high quality, and maintainable code based on requirements and design specifications
·  Optimize solutions (ETL / data pipelines) to balance performance, functionality, cost, and other operational requirements
·  Conduct peer reviews for quality, consistency, and rigor for production level solution
·  Create design and development documentation based on standards for knowledge transfer, training, and maintenance
·  Define and promote best practices and standards for code management, automated testing, and deployments
·  Mentor and train junior team members
·  Assess and fix data pipeline issues to ensure performance and timeliness of execution
·  Lead data engineering efforts to modernize and replace legacy solutions and platforms
·  Partner with Data Engineering Manager, Product Owner and Data Analysts to create implementation plan, including assessments of timelines and complexity
·  Gather/organize large & complex data assets, and perform relevant analysis  
·  Actively contribute to Data Engineering community and define leading practices and frameworks
·  Communicate results and findings in a clear, structured manner to stakeholders at various levels
·  Remain up to date on the company’s standards, industry practices and emerging technologies 

Who You Are:

You are a savvy Data Engineer responsible for the technical development of best-in-class, cloud-first data engineering solutions to support our data product and AI teams. You revel in designing and implementing scalable cloud native data pipelines and data warehousing solutions. You excel in architecting both batch and event based data solutions. You have a keen eye to understand the business needs and deliver innovative and robust data engineering solutions. You thrive in a collaborative environment and love to build data pipelines that power our Data products. You are highly motivated, with a passion for data engineering, modeling, and cloud technologies.

Key Functional Requirements & Qualifications:

·  Experience working cross-functional teams to solve complex data architecture and engineering problems 
·  Demonstrated ability to learn new data and software engineering technologies in short amount of time
·  Able to work in a fast-paced, constantly evolving environment and manage multiple priorities  
·  Excellent written, verbal, and interpersonal skills with ability to communicate ideas, concepts and solutions to stakeholders at all levels
·  Service-oriented, flexible, and approachable team player
·  Fluent in English (Other languages a plus)

Key Technical Requirements & Qualifications:

·  Bachelor’s Degree or equivalent in Computer Science, Engineering, or relevant field 
·  2+ years of hands-on data engineering experience across both batch and event driven architecture
·  Strong coding skills in languages such as Python, Java, or Scala, as well as SQL
·  Strong grasp of distributed data processing tools such as Apache Kafka, as well as AWS Cloud Native Services
·  Experience with orchestration tools (such as Airflow, or Step Functions)
·  Demonstrated capability in data modeling and modern data warehouses (such as Snowflake, Bigquery, Redshift, or Synapse)
·  Nice to have: Experience with real time and streaming architecture with Kafka (or AWS cloud Native Services), and Spark Streaming

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.

Watch our ALL IN video and check out our Diversity Equity and Inclusion actions at sanofi.com !

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.