Accelerator Lead Data & AI Engineering (Paris)

Sanofi; Paris; Sur place; EUR 80 000 - 100 000; Plein temps

Résumé du poste

A leading global healthcare company is seeking a Lead Data Engineer to drive the design and operation of data pipelines essential for enterprise analytics. This position requires an experienced individual with a strong background in data engineering and software development. You will lead a team of Data and AI Engineers, ensuring compliance with industry regulations and optimizing systems for performance and cost-efficiency. The ideal candidate will possess excellent leadership skills and a passion for innovation in healthcare data solutions.

Qualifications

• 8 to 10 years experience in data engineering and analytics.
• Strong experience in production-ready software development.
• Experience with compliance in healthcare settings is a plus.

Responsabilités

• Lead the team of Data and AI Engineers in achieving project goals.
• Design and implement optimized data modules and pipelines.
• Collaborate with business teams to translate needs into technical solutions.

Connaissances

Data Engineering

Agile Development

Team Leadership

Problem Solving

Data Governance

Cloud Computing

Communication

Formation

Bachelor’s Degree in Computer Science, Engineering, or relevant field

Outils

AWS

SQL

Python

GitHub

Snowflake

Apache Airflow

Description du poste

Overview

At Sanofi, we’re committed to providing the next‑gen healthcare that patients and customers need. It’s about harnessing data insights and leveraging AI responsibly to search deeper and solve sooner than ever before. Join our digital accelerator commercial team as Lead Data Engineer and you can help make it happen.

In this role you will:

• Work with business teams to understand requirements, and translate them into technical needs.
• Support operations with the appropriate mindset‑oriented Operation Excellence.
• Enforce compliance requirements of the solution in regards of GxP regulation.
• Work in transverse with Cloud & Data architects, Product Owners, Scrum Masters, Development teams and External Partners.
• Work with product owner to build the vision and challenge solutions.
• Design and develop optimized modules meeting reliability, reusability, latency & performance & requirements.
• Support the Data modules engineers for designing optimized data models.
• Define support models and be responsible for build and run activities.
• Build, lead, manage and articulate a team of data and AI engineers.
• Continuous support to help team members throughout their personal and professional developments.
• Adapt the modules to optimize the running costs.
• Participate to the community of practice and act as a leader in the community.
• Mentor the juniors and senior practitioners.

You are a dynamic experienced Data Engineer lead interested in challenging the status quo to ensure the seamless creation and operation of the data pipelines that are needed for the enterprise data and analytics initiatives following industry standard practices and tools for the betterment of our global patients and customers.

You are a valued influencer and leader who has contributed to making key datasets available to data scientists, analysts, and consumers throughout the enterprise to meet vital business use needs. You have a keen eye for improvement opportunities while continuing to fully comply with all data quality, security, and governance standards.

Experience

• 8 to 10 years experience.
• Experience developing deployable code and deploying data pipelines and data models in product‑focused development under an agile environment.
• Strong experience in production‑ready software development.
• Excellent management and articulation of a team of Data and AI Engineers.
• Continuous support to help team members throughout their personal and professional development.
• Experience in a healthcare company is a strong plus.
• Experience on working within compliance (e.g.: quality, regulatory – data privacy, GxP, SOX) and cybersecurity requirements is a plus.
• Excellent written and verbal communication skills.
• Experience working with multiple teams to drive alignment and results.
• Service‑oriented, flexible, positive team player.
• Self‑motivated, takes initiative.
• Problem solving & critical thinking.

Technical Skills

• Experience with AWS cloud services (Azure is a plus).
• Strong knowledge of SQL and relational database technologies/concepts.
• Experience working with data models and query tuning.
• Experience in Data warehousing solutions (Snowflake).
• Experience in Integration Services (IICS, Tibco a plus).
• Working knowledge of scripting languages (Python, R a plus).
• Experience with Source Code Management Tools (GitHub a plus).
• Experience with vector database and LLM (e.g.: Pinecone, AWS Bedrock, Snowflake Cortex).
• Experience with timeseries database and Graph database (e.g.: TigerDB, Neo4J).
• Experience using orchestration to create pipelines (e.g. Apache Airflow).
• Experience with Product Management Tools (JIRA, Confluence a plus).
• Familiarity with Service Management Tools (ServiceNow a plus).
• Strong experience in automation tools and methodologies specifically using GitHub Actions, Terraform, Ansible.
• Experience with programming languages such as JSON, YAML, ShellScripting.
• Experience with backup system like NetBackup & CommVault.
• Good knowledge of ServiceNow, monitoring tools such as Splunk, Datadog, BPPM and experience in FinOps practice.
• Experience with a wide variety of data sources, such as structured and unstructured data, IoT data.
• Good knowledge of cybersecurity best practices.
• Relevant cloud certifications (AWS, Azure, Snowflake, IICS) are a plus.
• Familiarity with Visualization Tools (PowerBI, Tableau a plus).

Education

Bachelor’s Degree or equivalent in Computer Science, Engineering, or relevant field.

Equal Opportunity

At Sanofi, we provide equal opportunities to all regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, or gender identity.