Posted on 
Aug 1

Scientific Data Engineer

As a Scientific Data Manager, you will drive the strategy for management of a diverse range of experimental datasets across the Mellizyme R&D activities. Working closely with lab biologists, you will be responsible for requirements gathering, development of ETL pipelines and administration of data storage infrastructure. While some experience in the life sciences would be beneficial, the ability to learn quickly and adapt to changing requirements are more important. You will be involved in activities such as:
- Acting as primary contact with lab biologists to understand their data and metadata storage and access requirements.
- Developing and maintaining our data management platform, which is currently based on the commercial software package Benchling and storage with Google Cloud.
- Developing ETL pipelines, allowing for the automation of data capture directly from lab analytical instruments.
- Training colleagues in the use of data management solutions.
- Keeping abreast of current scientific data management best practices and bringing these into the company.
- Act as a point of contact with external software providers.

We would like to hear from you if you have:
- Strong technical background, including skills in Python and related data science libraries, relational, graph and document databases.
- A degree in computer science, bioinformatics, or a similar field.
- Relevant prior experience in (scientific) data management.
- Excellent interpersonal skills, with demonstrable evidence of working collaboratively in an interdisciplinary environment.
- Experience with version control systems such as Git.
- Prior skills in automated testing.
- Experience with cloud computing, ideally Google Cloud.
- An understanding of data security issues.

Cherries on the cake would be:
- Experience in biotechnology or life sciences.
- Experience in CI/CD.
- Knowledge of FAIR Data principles.
- Experience in software development project management.
- Prior team-leadership experience.
- Previous start-up experience.

Description

As a Scientific Data Manager, you will drive the strategy for management of a diverse range of experimental datasets across the Mellizyme R&D activities. Working closely with lab biologists, you will be responsible for requirements gathering, development of ETL pipelines and administration of data storage infrastructure. While some experience in the life sciences would be beneficial, the ability to learn quickly and adapt to changing requirements are more important. You will be involved in activities such as:
- Acting as primary contact with lab biologists to understand their data and metadata storage and access requirements.
- Developing and maintaining our data management platform, which is currently based on the commercial software package Benchling and storage with Google Cloud.
- Developing ETL pipelines, allowing for the automation of data capture directly from lab analytical instruments.
- Training colleagues in the use of data management solutions.
- Keeping abreast of current scientific data management best practices and bringing these into the company.
- Act as a point of contact with external software providers.

We would like to hear from you if you have:
- Strong technical background, including skills in Python and related data science libraries, relational, graph and document databases.
- A degree in computer science, bioinformatics, or a similar field.
- Relevant prior experience in (scientific) data management.
- Excellent interpersonal skills, with demonstrable evidence of working collaboratively in an interdisciplinary environment.
- Experience with version control systems such as Git.
- Prior skills in automated testing.
- Experience with cloud computing, ideally Google Cloud.
- An understanding of data security issues.

Cherries on the cake would be:
- Experience in biotechnology or life sciences.
- Experience in CI/CD.
- Knowledge of FAIR Data principles.
- Experience in software development project management.
- Prior team-leadership experience.
- Previous start-up experience.

Responsibilities

Requirements

Offer

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