Lead Data and AI Engineer

Reference no. R2867104

Position title: Lead Data and AI Engineer

Department: US Commercial  Data Engineering

Location: Toronto, ON

About the job

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.

Who You Are:

You are a hands-on data and AI engineering leader with a strong background in building and operating data pipelines and platforms in complex enterprise environments. You bring a blend of technical depth, architectural thinking, and people leadership. You are comfortable guiding a team, partnering with stakeholders, and translating business needs into scalable and reliable data solutions.

You care about engineering quality, operational excellence, and continuous improvement. You have experience working across cross-functional teams and know how to balance delivery, governance, and long-term platform sustainability.

In this role, you will report directly to the Head of Data Engineering, Commercial US. You will provide architectural leadership and technical know-how across data pipeline construction, execution, and operations. You will work closely with teams across Data, Digital, Infrastructure, Cloud, Security, Agile, and key business stakeholders. You will also have direct people management responsibilities and the opportunity to shape and grow your team.

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.

About Sanofi 

We’re an R&D-driven, AI-powered biopharma company committed to improving people’s lives and delivering compelling growth. Our deep understanding of the immune system – and innovative pipeline – enables us to invent medicines and vaccines that treat and protect millions of people around the world. Together, we chase the miracles of science to improve people’s lives.

Main Responsibilities:

Lead, mentor, and develop a team of data engineers while fostering strong engineering practices, accountability, collaboration, and continuous improvement

Design, build, deploy, and support scalable data pipelines and data products that enable analytics, AI/ML, and commercial business use cases

Lead discovery, solution design, and technical planning discussions with business, analytics, AI, and technology teams

Manage team delivery, priorities, capacity planning, and execution across multiple concurrent data engineering initiatives

Design, develop, test, and optimize scalable data engineering solutions and reusable data assets that support analytics, AI/ML, and business-critical workflows across global platforms

Partner with technical and non-technical stakeholders to clarify ambiguous business needs, shape solution approaches, and translate requirements into scalable data engineering solutions

Provide architectural and technical leadership across data pipeline orchestration, distributed processing, cloud-native platforms, and data integration patterns

Drive operational excellence across production data assets, including monitoring, troubleshooting, incident response, release management, and continuous improvement

Identify opportunities to automate, simplify, standardize, and optimize data engineering processes, reusable assets, and platform capabilities

Collaborate within cross-functional agile teams and partner with internal and external stakeholders to deliver high-quality data engineering solutions

Contribute to and evolve data engineering standards, best practices, and community knowledge sharing across the organization

Stay current with emerging technologies, industry trends, and modern data engineering practices to continuously improve platform capabilities and engineering effectiveness

About you

Qualifications:

Minimum 8 years of experience in data engineering, analytics/AI engineering, or data platform development

Minimum 2 years leading or managing engineering teams/projects

Demonstrated experience designing, building, and operating scalable data pipelines, data platforms, and distributed processing solutions using technologies such as Spark, Kafka, Snowflake, Hadoop, or similar

Strong experience with cloud-native data engineering and modern ETL/ELT solutions, preferably within Snowflake / AWS-based environments; Informatica/IICS experience preferred

Advanced SQL and data modeling skills, with working knowledge of Python and scripting languages; Scala or Java is a plus

Experience with batch, near real-time, and streaming data architectures, as well as modern data warehouse, lake, and lakehouse concepts including data mesh principles

Strong understanding of data architecture, scalability, reliability, performance optimization, and operational support for enterprise-grade data platforms

Demonstrated ability to work with technical and non-technical stakeholders to navigate ambiguity, identify underlying business needs, and translate them into scalable technical solutions and execution plans

Strong communication, facilitation, and stakeholder management skills, with the ability to influence decisions and communicate complex technical concepts to diverse audiences

Experience partnering with cross-functional teams including analytics, AI/ML, product, infrastructure, security, governance, and business stakeholders

Experience operating in agile delivery environments with strong understanding of software engineering practices, CI/CD, release management, testing, and operational support

Experience leading engineering teams through delivery execution, prioritization, mentoring, performance management, and continuous improvement initiatives

Bachelor’s or Master’s degree in Computer Science, Engineering, STEM, Business, or a related field, or equivalent practical experience

Nice to haves:

Experience in life sciences, healthcare, or pharmaceutical industries

Experience with Airflow, dbt or similar orchestration and transformation tooling

Familiarity with data governance, data quality, and commercial data domains such as omni-channel, pricing, customer engagement, or sales analytics

Experience working with external vendors and offshore/onshore delivery models

Why Choose Us?  

Bring the miracles of science to life alongside a supportive, future-focused team.

Discover endless opportunities to grow your talent and drive your career, whether it’s through a promotion or lateral move, at home or internationally.

Enjoy a thoughtful, well-crafted rewards package that recognizes your contribution and amplifies your impact.

Take good care of yourself and your family, with a wide range of health and wellbeing benefits including high-quality healthcare, prevention and wellness programs.

This position is for a new vacant role that is now open for applications.​

AI Usage

"Artificial Intelligence” refers to any systems that use automated processes, including algorithms and machine learning, to analyze data and make predictions, inferences, decisions, or recommendations without direct human involvement. These systems may process personal information to identify patterns, improve services, or support decision-making. The Company may use Artificial Intelligence for purposes including, but not limited to, resume screening and hiring, scheduling interviews or meetings, conducting surveys, matching skills with potential job openings, interview scoring, ensuring compliance with regulations applicable to our industry, and activities related to performance evaluation. Information collected and processed by the Company’s Artificial Intelligence systems may include the personal information detailed above and calendar availability. It excludes the information collected and processed for monitoring purposes. You should contact Human Resources if you have a question or concern regarding your personal information. You can also contact Canada’s Privacy Officer via Sanofi’s data subject request portal,   Data Subject Rights Webform . The   Data Subject Rights Webform  can also be used to request access or correction of your personal information and file a complaint.

Sanofi is an equal opportunity employer committed to diversity and inclusion. Our goal is to attract, develop and retain highly talented employees from diverse backgrounds, allowing us to benefit from a wide variety of experiences and perspectives. We welcome and encourage applications from all qualified applicants.  Accommodations for persons with disabilities required during the recruitment process are available upon request.

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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, ability or gender identity.

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

North America Applicants Only

The salary range for this position is:

158,200.00 - 208,200.00 (Includes target bonus) Final compensation will be determined based on demonstrated experience, skills, location, and other relevant factors. Employees may be eligible to participate in Company employee benefits programs, and additional benefits information can be found through the (CA) LINK OR (US) LINK .

La fourchette salariale pour ce poste est la suivante:

158,200.00 - 208,200.00 (Comprend le bonus cible) La rémunération finale sera déterminée en fonction de l'expérience démontrée, des compétences, du lieu de travail et d'autres facteurs pertinents. Les employés peuvent être admissibles à participer aux programmes d'avantages sociaux de l'entreprise, et des informations supplémentaires sur les avantages sociaux peuvent être trouvées via le lien