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Lab Data Technology Specialist - Nestlé Research

Nestlé -
Lausanne, VD

Soumettre votre candidature

Détails de l'emploi

100%

Avantages

Jours fériés payés
Congé parental payé
Réduction pour les employés
Logement
Caisse de pension

Qualifications

Informatique
Power BI
Gestion du personnel
R
Expérience en laboratoire
NoSQL
Git
Anglais
Java
Niveau Master
SQL
Niveau Licence
Compétences en communication
Graph databases
Python

Description complète du poste

Strategic Research Operations

Location: Lausanne, Switzerland
Work model: Hybrid / Full time 100%
Contract type / duration: Permanent

Shape the future through scientific breakthroughs and innovation.

As a Lab Data Technology Specialist at Nestlé Research within our Computational Sciences department, you will be responsible for reinforcing our laboratory data foundations to help unlock the full value of the data generated by our scientific instruments and laboratory systems. Sitting at the intersection of science, laboratory data, and modern data engineering, you will leverage latest data technologies and AI for coding tools to transform raw, heterogeneous scientific data into trusted, well-documented, and reusable data assets that accelerate impactful scientific research.

How you’ll make an impact as a Lab Data Technology Specialist

Partner with laboratory stakeholders. data domain owners, lab business analysts together with data architects and engineers to translate functional requirements into scalable, and well-documented technical solutions, ensuring alignment between scientific workflows and technological capabilities
Enable new and existing laboratory instruments end to end, from understanding the scientific workflow and data outputs to defining and establishing connectivity and data flow (LIMS, robotics, automation platforms, downstream systems), in collaboration with IT network, security specialists
Collaborate with internal and external professionals to propose and implement customizations to lab digital platforms used (LIMS, instrument integration, technology specific data processing, metadata capture) in view of efficiency, quality, traceability, and governance by design
Identify opportunities to increase value of lab data gathered across different sources by leveraging data technologies (data integrations, data warehousing, automated data quality checks, etc)
Support testing, deployment, change management, and continuous improvement of compliant, scalable lab solutions, including AI-enabled opportunities to strengthen data flows and unlock value from lab data

What will make you successful

Bachelor's or Master's degree in a scientific or computational discipline (e.g., Chemistry, life sciences, Bioinformatics, Cheminformatics, Data Engineering, Computer Science), or equivalent experience.
Solid experience in applying data engineering to scientific, laboratory data
Required technical skills
- - LIMS customization, data models, and integration.
  - Integrating lab instruments, applications, robots, and IoT with reference databases and data warehouses (e.g., Snowflake).
  - Solid grasp of the lab solutions ecosystem: ELN, CDS, LES, multi-omics pipelines, IoT-connected equipment, barcode systems, etc.
  - Programming (e.g., Python, R, Java, Groovy).
  - Data engineering and modeling — ETL/ELT (Airflow, dbt), APIs, orchestration, SQL/NoSQL — with engineering rigor (Git, CI/CD, testing, data quality, observability, reproducibility).
Nice-to-have technical skills
- - Semantic modeling, ontologies, and knowledge graphs (e.g., RDF/SPARQL, biomedical/chemical vocabularies).
  - FAIR data implementation, metadata management, and lineage tooling
  - Enabling AI/ML and analytics use cases on scientific data
  - Domain exposure in chemistry, biology, food, or omics
  - Reporting tools (e.g., DASH, Streamlit, Power BI) is an advantage
  - Leveraging Agentic AI to automate data engineering activities
Required non-technical skills
- - Strong problem-solving and hands-on mindset
  - Excellent communication and stakeholder management skills
  - Experience collaborating with external vendors and data professionals and driving delivery through others
  - Ability to work in cross-functional and international teams
  - Strong organizational and prioritization skills
  - Fluent spoken and written English

At Nestlé Research, we place people at the core of everything we do.

Our benefits are designed to support your growth and wellbeing, so you can thrive at work and in life:

Flexible working options, including hybrid work possibilities (for office based roles)
Paid holidays beyond legal requirements
Learning and development opportunities to grow your career
Performance based bonus
Healthcare contribution and access to the Employee Assistance Program
Strong employer contribution to your pension plan
Generous parental leave and comprehensive family support solutions
Attractive employee discounts across various products and services

What to expect from our hiring process

We are committed to an inclusive and respectful hiring experience and are happy to provide reasonable accommodations if needed. Our workplaces are fully accessible and supported by a strong safety culture, with modern installations and procedures to ensure a safe environment for everyone.

The hiring process typically includes a video interview with Talent Acquisition, an interview with the hiring team, and a final discussion and offer. We review applications as they are received and close the role once a strong list of relevant candidates is identified, so we encourage you to apply early. All information is treated confidentially.

Stay vigilant: Nestlé will only contact candidates via official company email addresses and will never ask for payments or sensitive personal information at any stage of the hiring process.

Ready to #BreakthroughTogether?

Apply now and shape the future through scientific breakthroughs and innovation.

#nestlecareerswitzerland

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data engineer emplois - pully, vd

Lab Data Technology Specialist - Nestlé Research

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Je souhaite recevoir la dernière alerte Emploi pour les postes de ce type : data engineer (pully, vd)

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