Job
- Level
- Lead
- Job Field
- Software, Data
- Employment Type
- Full Time
- Contract Type
- Permanent employment
- Salary
- 109.800 to 138.500€ gross/year
- Location
- Berlin
- Working Model
- Hybrid, Onsite
Job Summary
In this role, you will develop scalable data pipelines and cloud-based solutions to transform complex data into usable, AI-ready products while establishing technical standards and governance practices.
Job Technologies
Your role in the team
- Lead the design, architecture, and continuous evolution of scalable data pipelines, data products, and engineering frameworks that transform complex real-world data into trusted, reusable, and AI/ML-ready assets for evidence generation and decision-making.
- Develop and implement robust, cloud-based engineering solutions that improve reliability, scalability, security, transparency, and speed-to-insight across analytical and AI/ML use cases.
- Establish and advance engineering standards for data ingestion, transformation, orchestration, monitoring, metadata management, version control, and documentation, creating reusable capabilities that support long-term business and scientific needs.
- Führen Sie die verantwortungsvolle Einführung von KI-gestützten Engineering-Praktiken voran, indem Sie Governance, Validierung, Observability und Qualitätskontrollen in die Daten- und Plattformentwicklungsprozesse integrieren.
- Build and maintain quality-by-design frameworks that ensure data integrity, traceability, privacy, compliance, and operational excellence throughout the entire data lifecycle.
- Provide technical leadership and mentorship to Data Engineers and cross-functional technical teams, fostering a culture of collaboration, continuous learning, innovation, and engineering excellence.
- Partner closely with Data Scientists, Product Teams, Global Medical & Evidence colleagues, IT, and external collaborators to translate scientific and business challenges into scalable platform capabilities, reusable data products, and AI-enabled solutions.
- Contribute to the strategic direction of RWDS&AI by shaping platform roadmaps, engineering best practices, AI/ML enablement initiatives, and next-generation data capabilities, while representing the organization in internal and external technical communities.
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Our expectations of you
Qualifications
- You hold a PhD (preferred) or MSc in Data Engineering, Computer Science, Software Engineering, Data Science, Bioinformatics, Mathematics, Statistics, Physics, Engineering, Computational Science, or a related field.
- You have successfully led complex engineering initiatives, designed and scaled modern data platforms, and supported the growth of technical teams through mentoring and knowledge sharing.
- You possess deep expertise in Real-World Data (RWD) and can design scalable, reusable data solutions, define technical standards, evaluate data feasibility, and support complex research and AI/ML use cases.
- You are highly proficient in Python and SQL and have a proven ability to build maintainable, scalable, and production-ready engineering solutions that drive business value.
- You bring advanced expertise in Machine Learning Engineering, Software Engineering, and AI-enabled Platforms, including ML-ready data products, feature stores, model serving infrastructure, workflow orchestration, and production-grade analytics environments.
- You are a collaborative and strategic thinker with strong communication, stakeholder management, systems thinking, and problem-solving skills, and you communicate fluently in English, both written and spoken.
Experience
- You bring extensive professional experience in Data Engineering, Software Engineering, Platform Engineering, Analytics Engineering, or a similar technical discipline. Experience in healthcare, life sciences, or the pharmaceutical industry is a strong advantage.
- You have strong experience with Data Science Infrastructure, Data Modeling, Ontologies, Data Quality, and Validation Frameworks, ensuring reproducibility, interoperability, security, compliance, and scalability across modern cloud environments.
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What we offer
- We ensure your financial stability with a competitive salary between €109,800 and €138,500 per year (full-time) plus a variable component and a global equity-based cash plan. Your compensation is based on your qualifications, skills, and professional experience.
- Whether it's hybrid work models or part-time arrangements: Whenever it is possible, you will have the flexibility to work how, when and where it is best for you.
- Your family is a top priority. We offer caring company daycare centers at multiple locations, support in finding childcare, time off for the care of elderly or dependent family members, summer camps for children, and much more.
- We support your professional growth by providing access to learning and development opportunities, training programs through the Bayer Learning Academy, development dialogues, as well as coaching and mentoring programs.
- We promote health awareness and opportunities for self-care through various measures, such as free health checks with the company doctor.
- We embrace diversity by providing an inclusive work environment in which you are welcomed, supported, and encouraged to bring your whole self to work.
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Benefits
Work-Life-Integration
Health, Fitness & Fun
Higher Take-Home Pay
Topics You Will Work On
Job Locations
About Your Employer
Bayer AG
Bayer AG is a globally active company with core competencies in the life science fields of health and nutrition. We develop our products and services for the benefit of people and the planet, and are committed to addressing the global challenges of a constantly growing and aging world population.
Description
- Company Type
- Established Company
- Working Model
- Full Remote, Hybrid, Onsite
- Industry
- Pharmaceutical Sector, Chemical Industry, Biotech
Senior Lead Data Engineer
- Salary
- 109.800 to 138.500€ gross/yearEstimated net salary based on the gross salary in the job ad using tax class I.63.137 to 78.447 € net/year · Tax class I
- Location
- Berlin
- Working Model
- Hybrid, Onsite
- Diversity
- Open for all genders
- English Only
- English only required
