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Lab Data Technology Specialist - Nestlé Research

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Strategic Research Operations Location: Lausanne, Switzerland Work model: Hybrid / Full time 100% Contract type / duration: Permanent Shape the future through scientific breakthroughs and innovation.
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Education & alternatives
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
Apply at nestleHRprdRMK

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  • Java
  • Python
  • R
  • SQL
  • dbt
  • NoSQL
  • Power BI
  • Snowflake
  • Airflow
  • Streamlit
Where the posting names them
- 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).
- 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
- 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
- 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.

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Demand for Data Engineer roles

New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.

Weekly new Data Engineer postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 834, the most 1,326, and the latest week had 1,326.
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About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

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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Lausanne, CH

Strategic Research Operations Location: Lausanne, Switzerland Work model: Hybrid / Full time 100% Contract type / duration: Permanent Shape the future through scientific breakthroughs and innovation.
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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
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