Data Platform Engineer Analyst

Sanofi•Toronto, ON

3d•CA$100,500 - CA$150,500•Hybrid

About The Position

Ready to push the limits of what’s possible? Join Sanofi in one of our corporate functions and you can play a vital part in the performance of our entire business while helping to make an impact on millions around the world. 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. Who You Are: You are experienced data engineer with 1-3 years of experience who is interested in designing and developing comprehensive solutions to support and facilitate business operations. As an experienced data engineer you will play a crucial role in supporting the design, development, and optimization of data solutions. You are eager to learn and work closely with subject matter experts and senior team members, has a foundational understanding of data engineering principles, and is excited to contribute to our data-driven initiatives. Our vision for digital, data analytics and AI 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 adoption of artificial intelligence (AI) and machine learning (ML) solutions. This has enabled us to accelerate R&D, improve manufacturing and commercial performance, and bring novel drugs and vaccines to patients faster, all in order to improve health and save lives. The Digital Team at Sanofi is a unique data-driven team. We pride ourselves on being data obsessed and highly focused on using state of the art processes along with global technologies to drive impact to our solutions. We measure our insights and products based on how they perform across the globe and hold ourselves to the highest regard as our solutions can impact millions of lives. When tackling a problem, we do not just ask how we will create a solution, but how we will create a solution that reaches across the world with the best possible societal outcome. If you are passionate about improving the health and wellness of people across the globe using Data as your means, then you should look no farther than the Digital Team here at Sanofi. 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, published leaders and academics in machine learning to further develop your skillsets. Location: The Sanofi Digital Data Team uses a hybrid working model combining remote and office-based work. Position Summary: We are seeking an experienced data engineer to work with lead data engineers and global Sanofi data engineering teams to drive implementation of Data platform for Sanofi's advanced analytic, AI, and ML initiatives. As an experienced Data Engineer, you will play a critical role in helping design and implement globally scalable data engineering platform to make it easier for internal teams to start implementation of their user case and to enhance the lives of our global patients and customers. Your expertise will be instrumental in shaping the future of data-driven healthcare while providing technical leadership and mentorship to the data engineering team. In your role, you will be reporting to Senior Data Platform Manager, working closely with leadership to build data platform with inputs and feedback received from various teams across data foundations and business to address their immediate and long term needs.

Requirements

Bachelor's or master’s degree in computer science, Engineering, Mathematics, or a related field with 1 -3 years' experience.
Proven experience in data engineering or a related field.
Hands-on experience or strong familiarity with the modern data stack: Snowflake (cloud data warehousing), dbt (data transformation and modeling), Apache Airflow (workflow orchestration), and Power BI (business intelligence and visualization).
A strong passion for data engineering and a desire to learn and grow in the field.
Eagerness to work collaboratively in cross-functional teams and learn from experienced data professionals.
Basic understanding of data mesh concepts and an analytical mindset.
Excellent problem-solving skills and attention to detail.
Strong communication skills and a willingness to learn how to convey technical concepts to diverse stakeholders.
Interest in data integration technologies, cloud platforms, and modern data engineering tools including Snowflake, dbt, Airflow, and Power BI for end-to-end data solutions.

Responsibilities

Collaborate with data engineers and business teams to understand data requirements across bioinformatics, omics, clinical, and operational domains, translating them into scalable engineering solutions.
Design and develop data pipelines, architectures, and datasets that support efficient ingestion, transformation, and delivery of data to downstream consumers.
Build data transformation workflows using dbt for data modeling and Apache Airflow (MWAA) for pipeline orchestration, integrated with Snowflake as the core data warehouse.
Write efficient Snowflake SQL queries, implement data warehouse best practices, and optimize performance.
Use Python, Shell scripting, and Scala/Java for pipeline development and automation.
Create and maintain Power BI dashboards and reports that provide accurate insights to business stakeholders, ensuring data quality and accessibility.
Implement ETL/ELT pipelines using modern data integration patterns and tools, ensuring reliability and maintainability.
Contribute to the design and implementation of AWS-native data platform solutions that support production workloads.
Monitor and troubleshoot deployed data assets in production, identifying and resolving issues under guidance from senior team members.
Follow and apply global data engineering standards across architecture, data quality, governance, and platform consistency.
Share knowledge and best practices with the data engineering team, contributing to continuous improvement of data solutions.