Sr Specialist Scientific Data Engineering

Sr Specialist Scientific Data Engineering

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Flexible working arrangements - facilitating creativity and collaboration.

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Within our Computational Sciences department, as a Senior Specialist Scientific Data Engineering you will be responsible for delivering advanced data engineering capabilities to support Nestlé Research projects. Your main objective will be to design, build, and optimize robust data pipelines and architectures that enable efficient data access, integration, and analysis across diverse scientific domains (e.g., plant sciences, clinical research, and pet health and nutrition).

You will play a key role in enabling data-driven research by ensuring high-quality, scalable, and secure data infrastructure.

• Design and implement end-to-end scientific data pipelines, e.g. for Bioinformatics or Clinical or Omics, including data ingestion, transformation, storage, and analytics layers, tailored to scientific research use cases.
• Develop and deploy scalable data architectures on premise (Linux) or cloud platforms, ensuring performance, reliability, and compliance with data governance standards.
• Onboard and drive external developers as well as team up with other internal data specialists (data architects, data scientists, AI engineers, software developers...) to accelerate delivery in priority projects.
• Work in cross-functional project teams in a research environment to define project objectives and deliverables, evaluate the need and identify the right technical approaches to solve business need.
• Partner with other teams to gather functional requirements, and improve data quality, metadata management, and data discoverability.

• Bachelors or Master’s or PhD in Bioinformatics, or Computer Science combined with life sciences or a related field
• Significant professional experience - 7+ years - in designing and implementing data pipelines and architectures, in a research or scientific context, ideally in food or pharma industry
• You have the following expertise and technical skills:
  • Proficiency in data modeling, ETL/ELT processes, and distributed data systems.
  • Proficiency in Python and SQL for data manipulation and pipeline development.
  • Solid experience with cloud platforms (e.g., Azure) and orchestration tools (e.g., Airflow, ADF).
  • Solid experience with data lake and data warehouse technologies (e.g., Snowflake, DBT).
  • Experience working with Linux and container technologies (e.g., Openshift, Docker, Podman).
  • Experience with development frameworks (e.g., Agile, Dev Ops, Git, CI/CD).
  • Experience with Bioinformatics or Clinical or Omics data pipelines
  • Experience coding with AI assistance (e.g., Git Hub copilot)
  • Awareness of agentic architecture frameworks
• Experience collaborating with external teams and driving project streams through others to deliver results
• Experience in mentoring and guiding junior internal resources
• Excellent problem-solving, strong communication, stakeholder management and knowledge sharing skills
• Fluent spoken and written English

Exciting…