Lead Data Platform Engineer

ETL/ELT, and advanced tooling on AWS. Work hand-in-hand with cross-functional agile teams to architect and implement hybrid-cloud solutions for high-performance data processing. Implement data monitoring and alerting systems, partnering with DevOps teams to proactively identify and resolve platform issues. Ensure data security, compliance, and governance at every stage of the data platform following global standards and best practices. Establish and enforce global data engineering standards, ensuring alignment with data architecture, platform quality, and governance principles. Implement data warehouses, data lakes, and distributed processing technologies (Spark, Hadoop, Kafka) in production environments. Optimize SQL queries (Snowflake preferred) and both relational and non-relational databases for performance. Develop sophisticated data engineering solutions in Python, Shell scripting, and Scala/Java. Mentor junior engineers and foster a culture of collaboration and growth. Contribute to

the data engineering community by sharing insights and best practices. Qualifications Bachelor's/Master's in STEM or relevant field with 5-7 years of experience in data engineering, preferably in life sciences/pharma. Extensive background in designing, developing, and optimizing data and cloud solutions, including data pipelines and service-oriented architectures. Proven expertise in data integration technologies, ETL/ELT, and modern data engineering tools, with experience in implementing or supporting Data Mesh architectures. Experience with multimodal data systems (batch, near-real-time, streaming) and distributed architectures for large-scale processing on AWS, Snowflake, Spark, Hadoop, Kafka. Advanced knowledge of SQL, relational/non-relational databases, and query optimization. Proficiency in Python, Shell scripting, and Scala/Java. Experience managing cloud-native systems following IaC and DataOps principles (Terraform, CI/CD, orchestration). Experience with agile development processes and concepts. Excellent problem-solving, communication, presentation, and interpersonal skills. Ability to lead teams effectively and collaborate with stakeholders at all levels. Curiosity, commitment to continuous learning and improvement. Nice to Haves Experience in the life sciences/pharmaceutical industry. Familiarity with Data Mesh concepts such as data as a product, domain-driven design, and federated governance. Experience with visualization tools (PowerBI, Tableau) and project management tools (JIRA, Confluence). Salary Range: €59,600.00 - €89,400.00. Final compensation will be determined based on demonstrated experience, skills, location, and other relevant factors. 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.

Lead Data Platform Engineer Join Sanofi's data platform engineering team and play a key role in advancing analytics, AI, and ML initiatives that shape the future of healthcare. As a Lead Data Platform Engineer, you'll design and deliver scalable data platforms, mentor fellow engineers, and collaborate closely with leadership and teams to address both immediate and long-term business needs. Key Responsibilities Collaborate closely with business teams, data engineers, platform engineers, data scientists, and stakeholders to capture complex data needs and translate them into robust, scalable data engineering solutions. Lead and guide the design, build, and operations of robust data infrastructure on AWS Cloud, driving our data mesh architecture. Automate, optimize, and fine-tune platform provisioning, scaling, and maintenance tasks to boost operational efficiency, performance, scalability, and cost control. Lead the development and optimization of data pipelines using data integration