Job
- Level
- Lead
- Job Feld
- Software, Data
- Anstellung
- Vollzeit
- Vertragsart
- Unbefristetes Dienstverhältnis
- Gehalt
- 109.800 bis 138.500€ Brutto/Jahr
- Ort
- Berlin
- Arbeitsmodell
- Hybrid, Onsite
Job Zusammenfassung
In dieser Position entwickelst du skalierbare Datenpipelines und cloudbasierte Lösungen, um komplexe Daten in nutzbare, KI-fähige Produkte umzuwandeln, während du technische Standards und Governance-Praktiken etablierst.
Job Technologien
Deine Rolle im 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.
- Drive the responsible adoption of AI-enabled engineering practices by embedding governance, validation, observability, and quality controls into data and platform development processes.
- 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.
Unsere Erwartungen an dich
Qualifikationen
- 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.
Erfahrung
- 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.
Unser Angebot
- 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 loving 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 selfcare 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.
Benefits
Work-Life-Integration
Gesundheit, Fitness & Fun
Mehr Netto
Themen mit denen du dich im Job beschäftigst
Job Standorte
Das ist dein Arbeitgeber
Bayer AG
Die Bayer AG ist ein international agierendes Unternehmen, das sich auf die Bereiche Gesundheit und Ernährung spezialisiert hat. Unser Fokus liegt auf der Entwicklung von Produkten und Dienstleistungen, um den Menschen und dem Planeten Gutes zu tun. Gemeinsam arbeiten wir an Lösungen, um den globalen Herausforderungen einer wachsenden und alternden Weltbevölkerung gerecht zu werden.
Description
- Unternehmenstyp
- Etablierte Firma
- Arbeitsmodell
- Full Remote, Hybrid, Onsite
- Branche
- Pharma, Chemie, Biotech
Senior Lead Data Engineer
- Gehalt
- 109.800 bis 138.500€ Brutto/JahrNetto aus dem Bruttogehalt im Inserat mit Steuerklasse I umgerechnet.63.137 bis 78.447 € netto/Jahr · Steuerklasse I
- Ort
- Berlin
- Arbeitsmodell
- Hybrid, Onsite
- Diversität
- Für alle Personen geeignet (m/w/d)
- Nur Englisch
- Nur Englisch erforderlich
