赛诺菲
data engineer
data engineer
发布于 大约 15 小时前普通员工/个人贡献者
Barcelona, Spain
高级经验
全职员工
混合式弹性办公
本科
软件工程
SQL
ETL
GitHub
DBT
AI 估算 · 4k–6k
Senior data engineer role in Barcelona, with cloud skills, market salary around 4-6k EUR/month, typical for pharma.
职位详情
关于这个职位
This Data Engineer role at Sanofi involves designing and building data pipelines on cloud platforms (AWS, Snowflake, DBT) to support AI-driven digital transformation in R&D. You will work in an agile product team to deliver data products, collaborating with product owners and junior engineers. The position offers a hybrid work model in Barcelona.
最低要求
Experience: 5+ years in data engineering, software engineering, or related fields
Soft skills: Excellent communication and collaboration skills
Technical skills: Experience in cloud-based data platforms (AWS, Snowflake, DBT), scheduling/orchestration (Airflow is a plus), scripting languages (Python, Shell), SQL and relational databases, DevOps (GitHub, GitHub Actions, Terraform), data structures and algorithms, data modeling
Education: Bachelor’s degree in software engineering or related field, or equivalent work experience
Languages: Excellent English communication and writing
工作职责
Provide input into engineering feasibility of R&D Data/AI Products
Support planning, capacity, and resource estimates
Design, build, and maintain scalable ETL/ELT pipelines
Structure and provision data for modeling and discovery (filtering, tagging, joining, parsing, normalizing)
Collaborate with Product Owner and Scrum Master on progress and issues
Design, develop, and deploy APIs and data feeds
Optimize data workflows for performance and reliability
Oversee and support junior engineers in testing
Stay current on industry trends and best practices
Contribute to a culture of innovation and continuous learning
AI 洞察
优缺点分析
优点
- Work in a global healthcare company with a strong digital transformation focus, providing stability and impact.
- Exposure to cutting-edge cloud stack (AWS, Snowflake, DBT) and modern data practices.
- Hybrid work model in Barcelona, with collaborative agile team environment.
- Requires 5+ years experience and strong technical breadth across cloud, DevOps, and data engineering.
- Pharma industry may have strict data governance and compliance requirements.
- Experienced data engineers who enjoy building robust data pipelines in a mission-driven, agile environment.
缺点 / 挑战
暂无明显挑战项
角色解读
- Advance to Senior Data Engineer or Data Architect, leading complex data initiatives.
- Transition into Data Product Owner or AI/ML Engineer roles with deeper domain expertise.
- Opportunity to become a technical team lead or manager within the data & AI organization.
- Design and build scalable data pipelines (ETL/ELT) to ingest and process large volumes of structured and unstructured data on cloud platforms.
- Collaborate with product owners and scrum masters in an agile pod to deliver data products supporting R&D initiatives.
- Optimize data workflows and mentor junior engineers, ensuring high performance and reliability.
- Strong experience with cloud data platforms (AWS, Snowflake, DBT) and DevOps tools (GitHub, Terraform).
- Proficiency in Python, SQL, and shell scripting for data manipulation and automation.
- Solid understanding of data modeling, data structures, and algorithms.
申请策略
- Tailor your resume to demonstrate impact on R&D or scientific data use cases, even if from other industries.
- Prepare examples of optimizing data workflows and handling large-scale data challenges.
- Emphasize hands-on experience with AWS, Snowflake, DBT, and building production ETL/ELT pipelines.
- Showcase DevOps skills with GitHub Actions, Terraform, and CI/CD practices.
- Highlight any mentoring or cross-team collaboration experience.
- Deepen knowledge of Airflow for orchestration (listed as a plus).
- Brush up on data modeling techniques and data governance best practices.
面试指南
- Use STAR method (Situation, Task, Action, Result) for behavioral questions.
- For technical questions, structure answer by problem statement, approach, implementation details, and outcomes.
- Describe a complex data pipeline you designed and how you ensured scalability.
- How do you handle data quality and validation in ETL processes?
- Explain your experience with Snowflake and DBT. How would you design a data model for analytics?
- Tell us about a time you mentored a junior engineer. What approach did you take?
- How do you stay updated with emerging data technologies?
- Review AWS, Snowflake, and DBT documentation for best practices.
职位点评
79
综合评分
Stable pharma company, modern cloud stack, hybrid work, strong learning culture.
更适合这类人
Candidates prioritizing skill growth and cutting-edge tech over immediate compensation.
表现最好
成长发展
相对薄弱
薪资福利
薪资福利70
成长发展90
工作生活75
使命价值80
薪资福利
70中等
Salary is competitive for Barcelona but not disclosed; benefits not mentioned; overall moderate compensation fit.
薪资信号未披露（AI估算：4K-6K/月）
成长发展
90较高
Strong emphasis on cloud/DevOps tech stack, mentoring, and continuous learning; good growth potential.
技术前沿前沿/新兴技术
技术栈AWS、Snowflake、DBT、Python、Airflow、Terraform、GitHub Actions
成长机会mentor、continuous learning、innovation
业务类型ambiguous
工作生活
75中等
Hybrid work mode offers flexibility; Barcelona location is attractive but office location not specified; no WLB signals.
工作模式混合式弹性办公
办公地点未明确
加班情况未提及（无法判断）
使命价值
80较高
Healthcare mission to improve lives, digital transformation in R&D, but innovation level is modern rather than pioneering.
行业发展稳定成熟行业
社会影响正向社会影响力较高
使命信号chase the miracles of science to improve people's lives
创新程度积极采用新技术
Watch Jobs